arrow_json/reader/
mod.rs

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17
18//! JSON reader
19//!
20//! This JSON reader allows JSON records to be read into the Arrow memory
21//! model. Records are loaded in batches and are then converted from the record-oriented
22//! representation to the columnar arrow data model.
23//!
24//! The reader ignores whitespace between JSON values, including `\n` and `\r`, allowing
25//! parsing of sequences of one or more arbitrarily formatted JSON values, including
26//! but not limited to newline-delimited JSON.
27//!
28//! # Basic Usage
29//!
30//! [`Reader`] can be used directly with synchronous data sources, such as [`std::fs::File`]
31//!
32//! ```
33//! # use arrow_schema::*;
34//! # use std::fs::File;
35//! # use std::io::BufReader;
36//! # use std::sync::Arc;
37//!
38//! let schema = Arc::new(Schema::new(vec![
39//!     Field::new("a", DataType::Float64, false),
40//!     Field::new("b", DataType::Float64, false),
41//!     Field::new("c", DataType::Boolean, true),
42//! ]));
43//!
44//! let file = File::open("test/data/basic.json").unwrap();
45//!
46//! let mut json = arrow_json::ReaderBuilder::new(schema).build(BufReader::new(file)).unwrap();
47//! let batch = json.next().unwrap().unwrap();
48//! ```
49//!
50//! # Async Usage
51//!
52//! The lower-level [`Decoder`] can be integrated with various forms of async data streams,
53//! and is designed to be agnostic to the various different kinds of async IO primitives found
54//! within the Rust ecosystem.
55//!
56//! For example, see below for how it can be used with an arbitrary `Stream` of `Bytes`
57//!
58//! ```
59//! # use std::task::{Poll, ready};
60//! # use bytes::{Buf, Bytes};
61//! # use arrow_schema::ArrowError;
62//! # use futures::stream::{Stream, StreamExt};
63//! # use arrow_array::RecordBatch;
64//! # use arrow_json::reader::Decoder;
65//! #
66//! fn decode_stream<S: Stream<Item = Bytes> + Unpin>(
67//!     mut decoder: Decoder,
68//!     mut input: S,
69//! ) -> impl Stream<Item = Result<RecordBatch, ArrowError>> {
70//!     let mut buffered = Bytes::new();
71//!     futures::stream::poll_fn(move |cx| {
72//!         loop {
73//!             if buffered.is_empty() {
74//!                 buffered = match ready!(input.poll_next_unpin(cx)) {
75//!                     Some(b) => b,
76//!                     None => break,
77//!                 };
78//!             }
79//!             let decoded = match decoder.decode(buffered.as_ref()) {
80//!                 Ok(decoded) => decoded,
81//!                 Err(e) => return Poll::Ready(Some(Err(e))),
82//!             };
83//!             let read = buffered.len();
84//!             buffered.advance(decoded);
85//!             if decoded != read {
86//!                 break
87//!             }
88//!         }
89//!
90//!         Poll::Ready(decoder.flush().transpose())
91//!     })
92//! }
93//!
94//! ```
95//!
96//! In a similar vein, it can also be used with tokio-based IO primitives
97//!
98//! ```
99//! # use std::sync::Arc;
100//! # use arrow_schema::{DataType, Field, Schema};
101//! # use std::pin::Pin;
102//! # use std::task::{Poll, ready};
103//! # use futures::{Stream, TryStreamExt};
104//! # use tokio::io::AsyncBufRead;
105//! # use arrow_array::RecordBatch;
106//! # use arrow_json::reader::Decoder;
107//! # use arrow_schema::ArrowError;
108//! fn decode_stream<R: AsyncBufRead + Unpin>(
109//!     mut decoder: Decoder,
110//!     mut reader: R,
111//! ) -> impl Stream<Item = Result<RecordBatch, ArrowError>> {
112//!     futures::stream::poll_fn(move |cx| {
113//!         loop {
114//!             let b = match ready!(Pin::new(&mut reader).poll_fill_buf(cx)) {
115//!                 Ok(b) if b.is_empty() => break,
116//!                 Ok(b) => b,
117//!                 Err(e) => return Poll::Ready(Some(Err(e.into()))),
118//!             };
119//!             let read = b.len();
120//!             let decoded = match decoder.decode(b) {
121//!                 Ok(decoded) => decoded,
122//!                 Err(e) => return Poll::Ready(Some(Err(e))),
123//!             };
124//!             Pin::new(&mut reader).consume(decoded);
125//!             if decoded != read {
126//!                 break;
127//!             }
128//!         }
129//!
130//!         Poll::Ready(decoder.flush().transpose())
131//!     })
132//! }
133//! ```
134//!
135
136use crate::StructMode;
137use std::io::BufRead;
138use std::sync::Arc;
139
140use chrono::Utc;
141use serde::Serialize;
142
143use arrow_array::timezone::Tz;
144use arrow_array::types::*;
145use arrow_array::{downcast_integer, make_array, RecordBatch, RecordBatchReader, StructArray};
146use arrow_data::ArrayData;
147use arrow_schema::{ArrowError, DataType, FieldRef, Schema, SchemaRef, TimeUnit};
148pub use schema::*;
149
150use crate::reader::boolean_array::BooleanArrayDecoder;
151use crate::reader::decimal_array::DecimalArrayDecoder;
152use crate::reader::list_array::ListArrayDecoder;
153use crate::reader::map_array::MapArrayDecoder;
154use crate::reader::null_array::NullArrayDecoder;
155use crate::reader::primitive_array::PrimitiveArrayDecoder;
156use crate::reader::string_array::StringArrayDecoder;
157use crate::reader::string_view_array::StringViewArrayDecoder;
158use crate::reader::struct_array::StructArrayDecoder;
159use crate::reader::tape::{Tape, TapeDecoder};
160use crate::reader::timestamp_array::TimestampArrayDecoder;
161
162mod boolean_array;
163mod decimal_array;
164mod list_array;
165mod map_array;
166mod null_array;
167mod primitive_array;
168mod schema;
169mod serializer;
170mod string_array;
171mod string_view_array;
172mod struct_array;
173mod tape;
174mod timestamp_array;
175
176/// A builder for [`Reader`] and [`Decoder`]
177pub struct ReaderBuilder {
178    batch_size: usize,
179    coerce_primitive: bool,
180    strict_mode: bool,
181    is_field: bool,
182    struct_mode: StructMode,
183
184    schema: SchemaRef,
185}
186
187impl ReaderBuilder {
188    /// Create a new [`ReaderBuilder`] with the provided [`SchemaRef`]
189    ///
190    /// This could be obtained using [`infer_json_schema`] if not known
191    ///
192    /// Any columns not present in `schema` will be ignored, unless `strict_mode` is set to true.
193    /// In this case, an error is returned when a column is missing from `schema`.
194    ///
195    /// [`infer_json_schema`]: crate::reader::infer_json_schema
196    pub fn new(schema: SchemaRef) -> Self {
197        Self {
198            batch_size: 1024,
199            coerce_primitive: false,
200            strict_mode: false,
201            is_field: false,
202            struct_mode: Default::default(),
203            schema,
204        }
205    }
206
207    /// Create a new [`ReaderBuilder`] that will parse JSON values of `field.data_type()`
208    ///
209    /// Unlike [`ReaderBuilder::new`] this does not require the root of the JSON data
210    /// to be an object, i.e. `{..}`, allowing for parsing of any valid JSON value(s)
211    ///
212    /// ```
213    /// # use std::sync::Arc;
214    /// # use arrow_array::cast::AsArray;
215    /// # use arrow_array::types::Int32Type;
216    /// # use arrow_json::ReaderBuilder;
217    /// # use arrow_schema::{DataType, Field};
218    /// // Root of JSON schema is a numeric type
219    /// let data = "1\n2\n3\n";
220    /// let field = Arc::new(Field::new("int", DataType::Int32, true));
221    /// let mut reader = ReaderBuilder::new_with_field(field.clone()).build(data.as_bytes()).unwrap();
222    /// let b = reader.next().unwrap().unwrap();
223    /// let values = b.column(0).as_primitive::<Int32Type>().values();
224    /// assert_eq!(values, &[1, 2, 3]);
225    ///
226    /// // Root of JSON schema is a list type
227    /// let data = "[1, 2, 3, 4, 5, 6, 7]\n[1, 2, 3]";
228    /// let field = Field::new_list("int", field.clone(), true);
229    /// let mut reader = ReaderBuilder::new_with_field(field).build(data.as_bytes()).unwrap();
230    /// let b = reader.next().unwrap().unwrap();
231    /// let list = b.column(0).as_list::<i32>();
232    ///
233    /// assert_eq!(list.offsets().as_ref(), &[0, 7, 10]);
234    /// let list_values = list.values().as_primitive::<Int32Type>();
235    /// assert_eq!(list_values.values(), &[1, 2, 3, 4, 5, 6, 7, 1, 2, 3]);
236    /// ```
237    pub fn new_with_field(field: impl Into<FieldRef>) -> Self {
238        Self {
239            batch_size: 1024,
240            coerce_primitive: false,
241            strict_mode: false,
242            is_field: true,
243            struct_mode: Default::default(),
244            schema: Arc::new(Schema::new([field.into()])),
245        }
246    }
247
248    /// Sets the batch size in rows to read
249    pub fn with_batch_size(self, batch_size: usize) -> Self {
250        Self { batch_size, ..self }
251    }
252
253    /// Sets if the decoder should coerce primitive values (bool and number) into string
254    /// when the Schema's column is Utf8 or LargeUtf8.
255    pub fn with_coerce_primitive(self, coerce_primitive: bool) -> Self {
256        Self {
257            coerce_primitive,
258            ..self
259        }
260    }
261
262    /// Sets if the decoder should return an error if it encounters a column not
263    /// present in `schema`. If `struct_mode` is `ListOnly` the value of
264    /// `strict_mode` is effectively `true`. It is required for all fields of
265    /// the struct to be in the list: without field names, there is no way to
266    /// determine which field is missing.
267    pub fn with_strict_mode(self, strict_mode: bool) -> Self {
268        Self {
269            strict_mode,
270            ..self
271        }
272    }
273
274    /// Set the [`StructMode`] for the reader, which determines whether structs
275    /// can be decoded from JSON as objects or lists. For more details refer to
276    /// the enum documentation. Default is to use `ObjectOnly`.
277    pub fn with_struct_mode(self, struct_mode: StructMode) -> Self {
278        Self {
279            struct_mode,
280            ..self
281        }
282    }
283
284    /// Create a [`Reader`] with the provided [`BufRead`]
285    pub fn build<R: BufRead>(self, reader: R) -> Result<Reader<R>, ArrowError> {
286        Ok(Reader {
287            reader,
288            decoder: self.build_decoder()?,
289        })
290    }
291
292    /// Create a [`Decoder`]
293    pub fn build_decoder(self) -> Result<Decoder, ArrowError> {
294        let (data_type, nullable) = match self.is_field {
295            false => (DataType::Struct(self.schema.fields.clone()), false),
296            true => {
297                let field = &self.schema.fields[0];
298                (field.data_type().clone(), field.is_nullable())
299            }
300        };
301
302        let decoder = make_decoder(
303            data_type,
304            self.coerce_primitive,
305            self.strict_mode,
306            nullable,
307            self.struct_mode,
308        )?;
309
310        let num_fields = self.schema.flattened_fields().len();
311
312        Ok(Decoder {
313            decoder,
314            is_field: self.is_field,
315            tape_decoder: TapeDecoder::new(self.batch_size, num_fields),
316            batch_size: self.batch_size,
317            schema: self.schema,
318        })
319    }
320}
321
322/// Reads JSON data with a known schema directly into arrow [`RecordBatch`]
323///
324/// Lines consisting solely of ASCII whitespace are ignored
325pub struct Reader<R> {
326    reader: R,
327    decoder: Decoder,
328}
329
330impl<R> std::fmt::Debug for Reader<R> {
331    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
332        f.debug_struct("Reader")
333            .field("decoder", &self.decoder)
334            .finish()
335    }
336}
337
338impl<R: BufRead> Reader<R> {
339    /// Reads the next [`RecordBatch`] returning `Ok(None)` if EOF
340    fn read(&mut self) -> Result<Option<RecordBatch>, ArrowError> {
341        loop {
342            let buf = self.reader.fill_buf()?;
343            if buf.is_empty() {
344                break;
345            }
346            let read = buf.len();
347
348            let decoded = self.decoder.decode(buf)?;
349            self.reader.consume(decoded);
350            if decoded != read {
351                break;
352            }
353        }
354        self.decoder.flush()
355    }
356}
357
358impl<R: BufRead> Iterator for Reader<R> {
359    type Item = Result<RecordBatch, ArrowError>;
360
361    fn next(&mut self) -> Option<Self::Item> {
362        self.read().transpose()
363    }
364}
365
366impl<R: BufRead> RecordBatchReader for Reader<R> {
367    fn schema(&self) -> SchemaRef {
368        self.decoder.schema.clone()
369    }
370}
371
372/// A low-level interface for reading JSON data from a byte stream
373///
374/// See [`Reader`] for a higher-level interface for interface with [`BufRead`]
375///
376/// The push-based interface facilitates integration with sources that yield arbitrarily
377/// delimited bytes ranges, such as [`BufRead`], or a chunked byte stream received from
378/// object storage
379///
380/// ```
381/// # use std::io::BufRead;
382/// # use arrow_array::RecordBatch;
383/// # use arrow_json::reader::{Decoder, ReaderBuilder};
384/// # use arrow_schema::{ArrowError, SchemaRef};
385/// #
386/// fn read_from_json<R: BufRead>(
387///     mut reader: R,
388///     schema: SchemaRef,
389/// ) -> Result<impl Iterator<Item = Result<RecordBatch, ArrowError>>, ArrowError> {
390///     let mut decoder = ReaderBuilder::new(schema).build_decoder()?;
391///     let mut next = move || {
392///         loop {
393///             // Decoder is agnostic that buf doesn't contain whole records
394///             let buf = reader.fill_buf()?;
395///             if buf.is_empty() {
396///                 break; // Input exhausted
397///             }
398///             let read = buf.len();
399///             let decoded = decoder.decode(buf)?;
400///
401///             // Consume the number of bytes read
402///             reader.consume(decoded);
403///             if decoded != read {
404///                 break; // Read batch size
405///             }
406///         }
407///         decoder.flush()
408///     };
409///     Ok(std::iter::from_fn(move || next().transpose()))
410/// }
411/// ```
412pub struct Decoder {
413    tape_decoder: TapeDecoder,
414    decoder: Box<dyn ArrayDecoder>,
415    batch_size: usize,
416    is_field: bool,
417    schema: SchemaRef,
418}
419
420impl std::fmt::Debug for Decoder {
421    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
422        f.debug_struct("Decoder")
423            .field("schema", &self.schema)
424            .field("batch_size", &self.batch_size)
425            .finish()
426    }
427}
428
429impl Decoder {
430    /// Read JSON objects from `buf`, returning the number of bytes read
431    ///
432    /// This method returns once `batch_size` objects have been parsed since the
433    /// last call to [`Self::flush`], or `buf` is exhausted. Any remaining bytes
434    /// should be included in the next call to [`Self::decode`]
435    ///
436    /// There is no requirement that `buf` contains a whole number of records, facilitating
437    /// integration with arbitrary byte streams, such as those yielded by [`BufRead`]
438    pub fn decode(&mut self, buf: &[u8]) -> Result<usize, ArrowError> {
439        self.tape_decoder.decode(buf)
440    }
441
442    /// Serialize `rows` to this [`Decoder`]
443    ///
444    /// This provides a simple way to convert [serde]-compatible datastructures into arrow
445    /// [`RecordBatch`].
446    ///
447    /// Custom conversion logic as described in [arrow_array::builder] will likely outperform this,
448    /// especially where the schema is known at compile-time, however, this provides a mechanism
449    /// to get something up and running quickly
450    ///
451    /// It can be used with [`serde_json::Value`]
452    ///
453    /// ```
454    /// # use std::sync::Arc;
455    /// # use serde_json::{Value, json};
456    /// # use arrow_array::cast::AsArray;
457    /// # use arrow_array::types::Float32Type;
458    /// # use arrow_json::ReaderBuilder;
459    /// # use arrow_schema::{DataType, Field, Schema};
460    /// let json = vec![json!({"float": 2.3}), json!({"float": 5.7})];
461    ///
462    /// let schema = Schema::new(vec![Field::new("float", DataType::Float32, true)]);
463    /// let mut decoder = ReaderBuilder::new(Arc::new(schema)).build_decoder().unwrap();
464    ///
465    /// decoder.serialize(&json).unwrap();
466    /// let batch = decoder.flush().unwrap().unwrap();
467    /// assert_eq!(batch.num_rows(), 2);
468    /// assert_eq!(batch.num_columns(), 1);
469    /// let values = batch.column(0).as_primitive::<Float32Type>().values();
470    /// assert_eq!(values, &[2.3, 5.7])
471    /// ```
472    ///
473    /// Or with arbitrary [`Serialize`] types
474    ///
475    /// ```
476    /// # use std::sync::Arc;
477    /// # use arrow_json::ReaderBuilder;
478    /// # use arrow_schema::{DataType, Field, Schema};
479    /// # use serde::Serialize;
480    /// # use arrow_array::cast::AsArray;
481    /// # use arrow_array::types::{Float32Type, Int32Type};
482    /// #
483    /// #[derive(Serialize)]
484    /// struct MyStruct {
485    ///     int32: i32,
486    ///     float: f32,
487    /// }
488    ///
489    /// let schema = Schema::new(vec![
490    ///     Field::new("int32", DataType::Int32, false),
491    ///     Field::new("float", DataType::Float32, false),
492    /// ]);
493    ///
494    /// let rows = vec![
495    ///     MyStruct{ int32: 0, float: 3. },
496    ///     MyStruct{ int32: 4, float: 67.53 },
497    /// ];
498    ///
499    /// let mut decoder = ReaderBuilder::new(Arc::new(schema)).build_decoder().unwrap();
500    /// decoder.serialize(&rows).unwrap();
501    ///
502    /// let batch = decoder.flush().unwrap().unwrap();
503    ///
504    /// // Expect batch containing two columns
505    /// let int32 = batch.column(0).as_primitive::<Int32Type>();
506    /// assert_eq!(int32.values(), &[0, 4]);
507    ///
508    /// let float = batch.column(1).as_primitive::<Float32Type>();
509    /// assert_eq!(float.values(), &[3., 67.53]);
510    /// ```
511    ///
512    /// Or even complex nested types
513    ///
514    /// ```
515    /// # use std::collections::BTreeMap;
516    /// # use std::sync::Arc;
517    /// # use arrow_array::StructArray;
518    /// # use arrow_cast::display::{ArrayFormatter, FormatOptions};
519    /// # use arrow_json::ReaderBuilder;
520    /// # use arrow_schema::{DataType, Field, Fields, Schema};
521    /// # use serde::Serialize;
522    /// #
523    /// #[derive(Serialize)]
524    /// struct MyStruct {
525    ///     int32: i32,
526    ///     list: Vec<f64>,
527    ///     nested: Vec<Option<Nested>>,
528    /// }
529    ///
530    /// impl MyStruct {
531    ///     /// Returns the [`Fields`] for [`MyStruct`]
532    ///     fn fields() -> Fields {
533    ///         let nested = DataType::Struct(Nested::fields());
534    ///         Fields::from([
535    ///             Arc::new(Field::new("int32", DataType::Int32, false)),
536    ///             Arc::new(Field::new_list(
537    ///                 "list",
538    ///                 Field::new("element", DataType::Float64, false),
539    ///                 false,
540    ///             )),
541    ///             Arc::new(Field::new_list(
542    ///                 "nested",
543    ///                 Field::new("element", nested, true),
544    ///                 true,
545    ///             )),
546    ///         ])
547    ///     }
548    /// }
549    ///
550    /// #[derive(Serialize)]
551    /// struct Nested {
552    ///     map: BTreeMap<String, Vec<String>>
553    /// }
554    ///
555    /// impl Nested {
556    ///     /// Returns the [`Fields`] for [`Nested`]
557    ///     fn fields() -> Fields {
558    ///         let element = Field::new("element", DataType::Utf8, false);
559    ///         Fields::from([
560    ///             Arc::new(Field::new_map(
561    ///                 "map",
562    ///                 "entries",
563    ///                 Field::new("key", DataType::Utf8, false),
564    ///                 Field::new_list("value", element, false),
565    ///                 false, // sorted
566    ///                 false, // nullable
567    ///             ))
568    ///         ])
569    ///     }
570    /// }
571    ///
572    /// let data = vec![
573    ///     MyStruct {
574    ///         int32: 34,
575    ///         list: vec![1., 2., 34.],
576    ///         nested: vec![
577    ///             None,
578    ///             Some(Nested {
579    ///                 map: vec![
580    ///                     ("key1".to_string(), vec!["foo".to_string(), "bar".to_string()]),
581    ///                     ("key2".to_string(), vec!["baz".to_string()])
582    ///                 ].into_iter().collect()
583    ///             })
584    ///         ]
585    ///     },
586    ///     MyStruct {
587    ///         int32: 56,
588    ///         list: vec![],
589    ///         nested: vec![]
590    ///     },
591    ///     MyStruct {
592    ///         int32: 24,
593    ///         list: vec![-1., 245.],
594    ///         nested: vec![None]
595    ///     }
596    /// ];
597    ///
598    /// let schema = Schema::new(MyStruct::fields());
599    /// let mut decoder = ReaderBuilder::new(Arc::new(schema)).build_decoder().unwrap();
600    /// decoder.serialize(&data).unwrap();
601    /// let batch = decoder.flush().unwrap().unwrap();
602    /// assert_eq!(batch.num_rows(), 3);
603    /// assert_eq!(batch.num_columns(), 3);
604    ///
605    /// // Convert to StructArray to format
606    /// let s = StructArray::from(batch);
607    /// let options = FormatOptions::default().with_null("null");
608    /// let formatter = ArrayFormatter::try_new(&s, &options).unwrap();
609    ///
610    /// assert_eq!(&formatter.value(0).to_string(), "{int32: 34, list: [1.0, 2.0, 34.0], nested: [null, {map: {key1: [foo, bar], key2: [baz]}}]}");
611    /// assert_eq!(&formatter.value(1).to_string(), "{int32: 56, list: [], nested: []}");
612    /// assert_eq!(&formatter.value(2).to_string(), "{int32: 24, list: [-1.0, 245.0], nested: [null]}");
613    /// ```
614    ///
615    /// Note: this ignores any batch size setting, and always decodes all rows
616    pub fn serialize<S: Serialize>(&mut self, rows: &[S]) -> Result<(), ArrowError> {
617        self.tape_decoder.serialize(rows)
618    }
619
620    /// True if the decoder is currently part way through decoding a record.
621    pub fn has_partial_record(&self) -> bool {
622        self.tape_decoder.has_partial_row()
623    }
624
625    /// The number of unflushed records, including the partially decoded record (if any).
626    pub fn len(&self) -> usize {
627        self.tape_decoder.num_buffered_rows()
628    }
629
630    /// True if there are no records to flush, i.e. [`Self::len`] is zero.
631    pub fn is_empty(&self) -> bool {
632        self.len() == 0
633    }
634
635    /// Flushes the currently buffered data to a [`RecordBatch`]
636    ///
637    /// Returns `Ok(None)` if no buffered data, i.e. [`Self::is_empty`] is true.
638    ///
639    /// Note: This will return an error if called part way through decoding a record,
640    /// i.e. [`Self::has_partial_record`] is true.
641    pub fn flush(&mut self) -> Result<Option<RecordBatch>, ArrowError> {
642        let tape = self.tape_decoder.finish()?;
643
644        if tape.num_rows() == 0 {
645            return Ok(None);
646        }
647
648        // First offset is null sentinel
649        let mut next_object = 1;
650        let pos: Vec<_> = (0..tape.num_rows())
651            .map(|_| {
652                let next = tape.next(next_object, "row").unwrap();
653                std::mem::replace(&mut next_object, next)
654            })
655            .collect();
656
657        let decoded = self.decoder.decode(&tape, &pos)?;
658        self.tape_decoder.clear();
659
660        let batch = match self.is_field {
661            true => RecordBatch::try_new(self.schema.clone(), vec![make_array(decoded)])?,
662            false => {
663                RecordBatch::from(StructArray::from(decoded)).with_schema(self.schema.clone())?
664            }
665        };
666
667        Ok(Some(batch))
668    }
669}
670
671trait ArrayDecoder: Send {
672    /// Decode elements from `tape` starting at the indexes contained in `pos`
673    fn decode(&mut self, tape: &Tape<'_>, pos: &[u32]) -> Result<ArrayData, ArrowError>;
674}
675
676macro_rules! primitive_decoder {
677    ($t:ty, $data_type:expr) => {
678        Ok(Box::new(PrimitiveArrayDecoder::<$t>::new($data_type)))
679    };
680}
681
682fn make_decoder(
683    data_type: DataType,
684    coerce_primitive: bool,
685    strict_mode: bool,
686    is_nullable: bool,
687    struct_mode: StructMode,
688) -> Result<Box<dyn ArrayDecoder>, ArrowError> {
689    downcast_integer! {
690        data_type => (primitive_decoder, data_type),
691        DataType::Null => Ok(Box::<NullArrayDecoder>::default()),
692        DataType::Float16 => primitive_decoder!(Float16Type, data_type),
693        DataType::Float32 => primitive_decoder!(Float32Type, data_type),
694        DataType::Float64 => primitive_decoder!(Float64Type, data_type),
695        DataType::Timestamp(TimeUnit::Second, None) => {
696            Ok(Box::new(TimestampArrayDecoder::<TimestampSecondType, _>::new(data_type, Utc)))
697        },
698        DataType::Timestamp(TimeUnit::Millisecond, None) => {
699            Ok(Box::new(TimestampArrayDecoder::<TimestampMillisecondType, _>::new(data_type, Utc)))
700        },
701        DataType::Timestamp(TimeUnit::Microsecond, None) => {
702            Ok(Box::new(TimestampArrayDecoder::<TimestampMicrosecondType, _>::new(data_type, Utc)))
703        },
704        DataType::Timestamp(TimeUnit::Nanosecond, None) => {
705            Ok(Box::new(TimestampArrayDecoder::<TimestampNanosecondType, _>::new(data_type, Utc)))
706        },
707        DataType::Timestamp(TimeUnit::Second, Some(ref tz)) => {
708            let tz: Tz = tz.parse()?;
709            Ok(Box::new(TimestampArrayDecoder::<TimestampSecondType, _>::new(data_type, tz)))
710        },
711        DataType::Timestamp(TimeUnit::Millisecond, Some(ref tz)) => {
712            let tz: Tz = tz.parse()?;
713            Ok(Box::new(TimestampArrayDecoder::<TimestampMillisecondType, _>::new(data_type, tz)))
714        },
715        DataType::Timestamp(TimeUnit::Microsecond, Some(ref tz)) => {
716            let tz: Tz = tz.parse()?;
717            Ok(Box::new(TimestampArrayDecoder::<TimestampMicrosecondType, _>::new(data_type, tz)))
718        },
719        DataType::Timestamp(TimeUnit::Nanosecond, Some(ref tz)) => {
720            let tz: Tz = tz.parse()?;
721            Ok(Box::new(TimestampArrayDecoder::<TimestampNanosecondType, _>::new(data_type, tz)))
722        },
723        DataType::Date32 => primitive_decoder!(Date32Type, data_type),
724        DataType::Date64 => primitive_decoder!(Date64Type, data_type),
725        DataType::Time32(TimeUnit::Second) => primitive_decoder!(Time32SecondType, data_type),
726        DataType::Time32(TimeUnit::Millisecond) => primitive_decoder!(Time32MillisecondType, data_type),
727        DataType::Time64(TimeUnit::Microsecond) => primitive_decoder!(Time64MicrosecondType, data_type),
728        DataType::Time64(TimeUnit::Nanosecond) => primitive_decoder!(Time64NanosecondType, data_type),
729        DataType::Duration(TimeUnit::Nanosecond) => primitive_decoder!(DurationNanosecondType, data_type),
730        DataType::Duration(TimeUnit::Microsecond) => primitive_decoder!(DurationMicrosecondType, data_type),
731        DataType::Duration(TimeUnit::Millisecond) => primitive_decoder!(DurationMillisecondType, data_type),
732        DataType::Duration(TimeUnit::Second) => primitive_decoder!(DurationSecondType, data_type),
733        DataType::Decimal128(p, s) => Ok(Box::new(DecimalArrayDecoder::<Decimal128Type>::new(p, s))),
734        DataType::Decimal256(p, s) => Ok(Box::new(DecimalArrayDecoder::<Decimal256Type>::new(p, s))),
735        DataType::Boolean => Ok(Box::<BooleanArrayDecoder>::default()),
736        DataType::Utf8 => Ok(Box::new(StringArrayDecoder::<i32>::new(coerce_primitive))),
737        DataType::Utf8View => Ok(Box::new(StringViewArrayDecoder::new(coerce_primitive))),
738        DataType::LargeUtf8 => Ok(Box::new(StringArrayDecoder::<i64>::new(coerce_primitive))),
739        DataType::List(_) => Ok(Box::new(ListArrayDecoder::<i32>::new(data_type, coerce_primitive, strict_mode, is_nullable, struct_mode)?)),
740        DataType::LargeList(_) => Ok(Box::new(ListArrayDecoder::<i64>::new(data_type, coerce_primitive, strict_mode, is_nullable, struct_mode)?)),
741        DataType::Struct(_) => Ok(Box::new(StructArrayDecoder::new(data_type, coerce_primitive, strict_mode, is_nullable, struct_mode)?)),
742        DataType::Binary | DataType::LargeBinary | DataType::FixedSizeBinary(_) => {
743            Err(ArrowError::JsonError(format!("{data_type} is not supported by JSON")))
744        }
745        DataType::Map(_, _) => Ok(Box::new(MapArrayDecoder::new(data_type, coerce_primitive, strict_mode, is_nullable, struct_mode)?)),
746        d => Err(ArrowError::NotYetImplemented(format!("Support for {d} in JSON reader")))
747    }
748}
749
750#[cfg(test)]
751mod tests {
752    use serde_json::json;
753    use std::fs::File;
754    use std::io::{BufReader, Cursor, Seek};
755
756    use arrow_array::cast::AsArray;
757    use arrow_array::{Array, BooleanArray, Float64Array, ListArray, StringArray, StringViewArray};
758    use arrow_buffer::{ArrowNativeType, Buffer};
759    use arrow_cast::display::{ArrayFormatter, FormatOptions};
760    use arrow_data::ArrayDataBuilder;
761    use arrow_schema::{Field, Fields};
762
763    use super::*;
764
765    fn do_read(
766        buf: &str,
767        batch_size: usize,
768        coerce_primitive: bool,
769        strict_mode: bool,
770        schema: SchemaRef,
771    ) -> Vec<RecordBatch> {
772        let mut unbuffered = vec![];
773
774        // Test with different batch sizes to test for boundary conditions
775        for batch_size in [1, 3, 100, batch_size] {
776            unbuffered = ReaderBuilder::new(schema.clone())
777                .with_batch_size(batch_size)
778                .with_coerce_primitive(coerce_primitive)
779                .build(Cursor::new(buf.as_bytes()))
780                .unwrap()
781                .collect::<Result<Vec<_>, _>>()
782                .unwrap();
783
784            for b in unbuffered.iter().take(unbuffered.len() - 1) {
785                assert_eq!(b.num_rows(), batch_size)
786            }
787
788            // Test with different buffer sizes to test for boundary conditions
789            for b in [1, 3, 5] {
790                let buffered = ReaderBuilder::new(schema.clone())
791                    .with_batch_size(batch_size)
792                    .with_coerce_primitive(coerce_primitive)
793                    .with_strict_mode(strict_mode)
794                    .build(BufReader::with_capacity(b, Cursor::new(buf.as_bytes())))
795                    .unwrap()
796                    .collect::<Result<Vec<_>, _>>()
797                    .unwrap();
798                assert_eq!(unbuffered, buffered);
799            }
800        }
801
802        unbuffered
803    }
804
805    #[test]
806    fn test_basic() {
807        let buf = r#"
808        {"a": 1, "b": 2, "c": true, "d": 1}
809        {"a": 2E0, "b": 4, "c": false, "d": 2, "e": 254}
810
811        {"b": 6, "a": 2.0, "d": 45}
812        {"b": "5", "a": 2}
813        {"b": 4e0}
814        {"b": 7, "a": null}
815        "#;
816
817        let schema = Arc::new(Schema::new(vec![
818            Field::new("a", DataType::Int64, true),
819            Field::new("b", DataType::Int32, true),
820            Field::new("c", DataType::Boolean, true),
821            Field::new("d", DataType::Date32, true),
822            Field::new("e", DataType::Date64, true),
823        ]));
824
825        let mut decoder = ReaderBuilder::new(schema.clone()).build_decoder().unwrap();
826        assert!(decoder.is_empty());
827        assert_eq!(decoder.len(), 0);
828        assert!(!decoder.has_partial_record());
829        assert_eq!(decoder.decode(buf.as_bytes()).unwrap(), 221);
830        assert!(!decoder.is_empty());
831        assert_eq!(decoder.len(), 6);
832        assert!(!decoder.has_partial_record());
833        let batch = decoder.flush().unwrap().unwrap();
834        assert_eq!(batch.num_rows(), 6);
835        assert!(decoder.is_empty());
836        assert_eq!(decoder.len(), 0);
837        assert!(!decoder.has_partial_record());
838
839        let batches = do_read(buf, 1024, false, false, schema);
840        assert_eq!(batches.len(), 1);
841
842        let col1 = batches[0].column(0).as_primitive::<Int64Type>();
843        assert_eq!(col1.null_count(), 2);
844        assert_eq!(col1.values(), &[1, 2, 2, 2, 0, 0]);
845        assert!(col1.is_null(4));
846        assert!(col1.is_null(5));
847
848        let col2 = batches[0].column(1).as_primitive::<Int32Type>();
849        assert_eq!(col2.null_count(), 0);
850        assert_eq!(col2.values(), &[2, 4, 6, 5, 4, 7]);
851
852        let col3 = batches[0].column(2).as_boolean();
853        assert_eq!(col3.null_count(), 4);
854        assert!(col3.value(0));
855        assert!(!col3.is_null(0));
856        assert!(!col3.value(1));
857        assert!(!col3.is_null(1));
858
859        let col4 = batches[0].column(3).as_primitive::<Date32Type>();
860        assert_eq!(col4.null_count(), 3);
861        assert!(col4.is_null(3));
862        assert_eq!(col4.values(), &[1, 2, 45, 0, 0, 0]);
863
864        let col5 = batches[0].column(4).as_primitive::<Date64Type>();
865        assert_eq!(col5.null_count(), 5);
866        assert!(col5.is_null(0));
867        assert!(col5.is_null(2));
868        assert!(col5.is_null(3));
869        assert_eq!(col5.values(), &[0, 254, 0, 0, 0, 0]);
870    }
871
872    #[test]
873    fn test_string() {
874        let buf = r#"
875        {"a": "1", "b": "2"}
876        {"a": "hello", "b": "shoo"}
877        {"b": "\t😁foo", "a": "\nfoobar\ud83d\ude00\u0061\u0073\u0066\u0067\u00FF"}
878
879        {"b": null}
880        {"b": "", "a": null}
881
882        "#;
883        let schema = Arc::new(Schema::new(vec![
884            Field::new("a", DataType::Utf8, true),
885            Field::new("b", DataType::LargeUtf8, true),
886        ]));
887
888        let batches = do_read(buf, 1024, false, false, schema);
889        assert_eq!(batches.len(), 1);
890
891        let col1 = batches[0].column(0).as_string::<i32>();
892        assert_eq!(col1.null_count(), 2);
893        assert_eq!(col1.value(0), "1");
894        assert_eq!(col1.value(1), "hello");
895        assert_eq!(col1.value(2), "\nfoobar😀asfgÿ");
896        assert!(col1.is_null(3));
897        assert!(col1.is_null(4));
898
899        let col2 = batches[0].column(1).as_string::<i64>();
900        assert_eq!(col2.null_count(), 1);
901        assert_eq!(col2.value(0), "2");
902        assert_eq!(col2.value(1), "shoo");
903        assert_eq!(col2.value(2), "\t😁foo");
904        assert!(col2.is_null(3));
905        assert_eq!(col2.value(4), "");
906    }
907
908    #[test]
909    fn test_long_string_view_allocation() {
910        // The JSON input contains field "a" with different string lengths.
911        // According to the implementation in the decoder:
912        // - For a string, capacity is only increased if its length > 12 bytes.
913        // Therefore, for:
914        // Row 1: "short" (5 bytes) -> capacity += 0
915        // Row 2: "this is definitely long" (24 bytes) -> capacity += 24
916        // Row 3: "hello" (5 bytes) -> capacity += 0
917        // Row 4: "\nfoobar😀asfgÿ" (17 bytes) -> capacity += 17
918        // Expected total capacity = 24 + 17 = 41
919        let expected_capacity: usize = 41;
920
921        let buf = r#"
922        {"a": "short", "b": "dummy"}
923        {"a": "this is definitely long", "b": "dummy"}
924        {"a": "hello", "b": "dummy"}
925        {"a": "\nfoobar😀asfgÿ", "b": "dummy"}
926        "#;
927
928        let schema = Arc::new(Schema::new(vec![
929            Field::new("a", DataType::Utf8View, true),
930            Field::new("b", DataType::LargeUtf8, true),
931        ]));
932
933        let batches = do_read(buf, 1024, false, false, schema);
934        assert_eq!(batches.len(), 1, "Expected one record batch");
935
936        // Get the first column ("a") as a StringViewArray.
937        let col_a = batches[0].column(0);
938        let string_view_array = col_a
939            .as_any()
940            .downcast_ref::<StringViewArray>()
941            .expect("Column should be a StringViewArray");
942
943        // Retrieve the underlying data buffer from the array.
944        // The builder pre-allocates capacity based on the sum of lengths for long strings.
945        let data_buffer = string_view_array.to_data().buffers()[0].len();
946
947        // Check that the allocated capacity is at least what we expected.
948        // (The actual buffer may be larger than expected due to rounding or internal allocation strategies.)
949        assert!(
950            data_buffer >= expected_capacity,
951            "Data buffer length ({data_buffer}) should be at least {expected_capacity}",
952        );
953
954        // Additionally, verify that the decoded values are correct.
955        assert_eq!(string_view_array.value(0), "short");
956        assert_eq!(string_view_array.value(1), "this is definitely long");
957        assert_eq!(string_view_array.value(2), "hello");
958        assert_eq!(string_view_array.value(3), "\nfoobar😀asfgÿ");
959    }
960
961    /// Test the memory capacity allocation logic when converting numeric types to strings.
962    #[test]
963    fn test_numeric_view_allocation() {
964        // For numeric types, the expected capacity calculation is as follows:
965        // Row 1: 123456789  -> Number converts to the string "123456789" (length 9), 9 <= 12, so no capacity is added.
966        // Row 2: 1000000000000 -> Treated as an I64 number; its string is "1000000000000" (length 13),
967        //                        which is >12 and its absolute value is > 999_999_999_999, so 13 bytes are added.
968        // Row 3: 3.1415 -> F32 number, a fixed estimate of 10 bytes is added.
969        // Row 4: 2.718281828459045 -> F64 number, a fixed estimate of 10 bytes is added.
970        // Total expected capacity = 13 + 10 + 10 = 33 bytes.
971        let expected_capacity: usize = 33;
972
973        let buf = r#"
974    {"n": 123456789}
975    {"n": 1000000000000}
976    {"n": 3.1415}
977    {"n": 2.718281828459045}
978    "#;
979
980        let schema = Arc::new(Schema::new(vec![Field::new("n", DataType::Utf8View, true)]));
981
982        let batches = do_read(buf, 1024, true, false, schema);
983        assert_eq!(batches.len(), 1, "Expected one record batch");
984
985        let col_n = batches[0].column(0);
986        let string_view_array = col_n
987            .as_any()
988            .downcast_ref::<StringViewArray>()
989            .expect("Column should be a StringViewArray");
990
991        // Check that the underlying data buffer capacity is at least the expected value.
992        let data_buffer = string_view_array.to_data().buffers()[0].len();
993        assert!(
994            data_buffer >= expected_capacity,
995            "Data buffer length ({data_buffer}) should be at least {expected_capacity}",
996        );
997
998        // Verify that the converted string values are correct.
999        // Note: The format of the number converted to a string should match the actual implementation.
1000        assert_eq!(string_view_array.value(0), "123456789");
1001        assert_eq!(string_view_array.value(1), "1000000000000");
1002        assert_eq!(string_view_array.value(2), "3.1415");
1003        assert_eq!(string_view_array.value(3), "2.718281828459045");
1004    }
1005
1006    #[test]
1007    fn test_string_with_uft8view() {
1008        let buf = r#"
1009        {"a": "1", "b": "2"}
1010        {"a": "hello", "b": "shoo"}
1011        {"b": "\t😁foo", "a": "\nfoobar\ud83d\ude00\u0061\u0073\u0066\u0067\u00FF"}
1012
1013        {"b": null}
1014        {"b": "", "a": null}
1015
1016        "#;
1017        let schema = Arc::new(Schema::new(vec![
1018            Field::new("a", DataType::Utf8View, true),
1019            Field::new("b", DataType::LargeUtf8, true),
1020        ]));
1021
1022        let batches = do_read(buf, 1024, false, false, schema);
1023        assert_eq!(batches.len(), 1);
1024
1025        let col1 = batches[0].column(0).as_string_view();
1026        assert_eq!(col1.null_count(), 2);
1027        assert_eq!(col1.value(0), "1");
1028        assert_eq!(col1.value(1), "hello");
1029        assert_eq!(col1.value(2), "\nfoobar😀asfgÿ");
1030        assert!(col1.is_null(3));
1031        assert!(col1.is_null(4));
1032        assert_eq!(col1.data_type(), &DataType::Utf8View);
1033
1034        let col2 = batches[0].column(1).as_string::<i64>();
1035        assert_eq!(col2.null_count(), 1);
1036        assert_eq!(col2.value(0), "2");
1037        assert_eq!(col2.value(1), "shoo");
1038        assert_eq!(col2.value(2), "\t😁foo");
1039        assert!(col2.is_null(3));
1040        assert_eq!(col2.value(4), "");
1041    }
1042
1043    #[test]
1044    fn test_complex() {
1045        let buf = r#"
1046           {"list": [], "nested": {"a": 1, "b": 2}, "nested_list": {"list2": [{"c": 3}, {"c": 4}]}}
1047           {"list": [5, 6], "nested": {"a": 7}, "nested_list": {"list2": []}}
1048           {"list": null, "nested": {"a": null}}
1049        "#;
1050
1051        let schema = Arc::new(Schema::new(vec![
1052            Field::new_list("list", Field::new("element", DataType::Int32, false), true),
1053            Field::new_struct(
1054                "nested",
1055                vec![
1056                    Field::new("a", DataType::Int32, true),
1057                    Field::new("b", DataType::Int32, true),
1058                ],
1059                true,
1060            ),
1061            Field::new_struct(
1062                "nested_list",
1063                vec![Field::new_list(
1064                    "list2",
1065                    Field::new_struct(
1066                        "element",
1067                        vec![Field::new("c", DataType::Int32, false)],
1068                        false,
1069                    ),
1070                    true,
1071                )],
1072                true,
1073            ),
1074        ]));
1075
1076        let batches = do_read(buf, 1024, false, false, schema);
1077        assert_eq!(batches.len(), 1);
1078
1079        let list = batches[0].column(0).as_list::<i32>();
1080        assert_eq!(list.len(), 3);
1081        assert_eq!(list.value_offsets(), &[0, 0, 2, 2]);
1082        assert_eq!(list.null_count(), 1);
1083        assert!(list.is_null(2));
1084        let list_values = list.values().as_primitive::<Int32Type>();
1085        assert_eq!(list_values.values(), &[5, 6]);
1086
1087        let nested = batches[0].column(1).as_struct();
1088        let a = nested.column(0).as_primitive::<Int32Type>();
1089        assert_eq!(list.null_count(), 1);
1090        assert_eq!(a.values(), &[1, 7, 0]);
1091        assert!(list.is_null(2));
1092
1093        let b = nested.column(1).as_primitive::<Int32Type>();
1094        assert_eq!(b.null_count(), 2);
1095        assert_eq!(b.len(), 3);
1096        assert_eq!(b.value(0), 2);
1097        assert!(b.is_null(1));
1098        assert!(b.is_null(2));
1099
1100        let nested_list = batches[0].column(2).as_struct();
1101        assert_eq!(nested_list.len(), 3);
1102        assert_eq!(nested_list.null_count(), 1);
1103        assert!(nested_list.is_null(2));
1104
1105        let list2 = nested_list.column(0).as_list::<i32>();
1106        assert_eq!(list2.len(), 3);
1107        assert_eq!(list2.null_count(), 1);
1108        assert_eq!(list2.value_offsets(), &[0, 2, 2, 2]);
1109        assert!(list2.is_null(2));
1110
1111        let list2_values = list2.values().as_struct();
1112
1113        let c = list2_values.column(0).as_primitive::<Int32Type>();
1114        assert_eq!(c.values(), &[3, 4]);
1115    }
1116
1117    #[test]
1118    fn test_projection() {
1119        let buf = r#"
1120           {"list": [], "nested": {"a": 1, "b": 2}, "nested_list": {"list2": [{"c": 3, "d": 5}, {"c": 4}]}}
1121           {"list": [5, 6], "nested": {"a": 7}, "nested_list": {"list2": []}}
1122        "#;
1123
1124        let schema = Arc::new(Schema::new(vec![
1125            Field::new_struct(
1126                "nested",
1127                vec![Field::new("a", DataType::Int32, false)],
1128                true,
1129            ),
1130            Field::new_struct(
1131                "nested_list",
1132                vec![Field::new_list(
1133                    "list2",
1134                    Field::new_struct(
1135                        "element",
1136                        vec![Field::new("d", DataType::Int32, true)],
1137                        false,
1138                    ),
1139                    true,
1140                )],
1141                true,
1142            ),
1143        ]));
1144
1145        let batches = do_read(buf, 1024, false, false, schema);
1146        assert_eq!(batches.len(), 1);
1147
1148        let nested = batches[0].column(0).as_struct();
1149        assert_eq!(nested.num_columns(), 1);
1150        let a = nested.column(0).as_primitive::<Int32Type>();
1151        assert_eq!(a.null_count(), 0);
1152        assert_eq!(a.values(), &[1, 7]);
1153
1154        let nested_list = batches[0].column(1).as_struct();
1155        assert_eq!(nested_list.num_columns(), 1);
1156        assert_eq!(nested_list.null_count(), 0);
1157
1158        let list2 = nested_list.column(0).as_list::<i32>();
1159        assert_eq!(list2.value_offsets(), &[0, 2, 2]);
1160        assert_eq!(list2.null_count(), 0);
1161
1162        let child = list2.values().as_struct();
1163        assert_eq!(child.num_columns(), 1);
1164        assert_eq!(child.len(), 2);
1165        assert_eq!(child.null_count(), 0);
1166
1167        let c = child.column(0).as_primitive::<Int32Type>();
1168        assert_eq!(c.values(), &[5, 0]);
1169        assert_eq!(c.null_count(), 1);
1170        assert!(c.is_null(1));
1171    }
1172
1173    #[test]
1174    fn test_map() {
1175        let buf = r#"
1176           {"map": {"a": ["foo", null]}}
1177           {"map": {"a": [null], "b": []}}
1178           {"map": {"c": null, "a": ["baz"]}}
1179        "#;
1180        let map = Field::new_map(
1181            "map",
1182            "entries",
1183            Field::new("key", DataType::Utf8, false),
1184            Field::new_list("value", Field::new("element", DataType::Utf8, true), true),
1185            false,
1186            true,
1187        );
1188
1189        let schema = Arc::new(Schema::new(vec![map]));
1190
1191        let batches = do_read(buf, 1024, false, false, schema);
1192        assert_eq!(batches.len(), 1);
1193
1194        let map = batches[0].column(0).as_map();
1195        let map_keys = map.keys().as_string::<i32>();
1196        let map_values = map.values().as_list::<i32>();
1197        assert_eq!(map.value_offsets(), &[0, 1, 3, 5]);
1198
1199        let k: Vec<_> = map_keys.iter().flatten().collect();
1200        assert_eq!(&k, &["a", "a", "b", "c", "a"]);
1201
1202        let list_values = map_values.values().as_string::<i32>();
1203        let lv: Vec<_> = list_values.iter().collect();
1204        assert_eq!(&lv, &[Some("foo"), None, None, Some("baz")]);
1205        assert_eq!(map_values.value_offsets(), &[0, 2, 3, 3, 3, 4]);
1206        assert_eq!(map_values.null_count(), 1);
1207        assert!(map_values.is_null(3));
1208
1209        let options = FormatOptions::default().with_null("null");
1210        let formatter = ArrayFormatter::try_new(map, &options).unwrap();
1211        assert_eq!(formatter.value(0).to_string(), "{a: [foo, null]}");
1212        assert_eq!(formatter.value(1).to_string(), "{a: [null], b: []}");
1213        assert_eq!(formatter.value(2).to_string(), "{c: null, a: [baz]}");
1214    }
1215
1216    #[test]
1217    fn test_not_coercing_primitive_into_string_without_flag() {
1218        let schema = Arc::new(Schema::new(vec![Field::new("a", DataType::Utf8, true)]));
1219
1220        let buf = r#"{"a": 1}"#;
1221        let err = ReaderBuilder::new(schema.clone())
1222            .with_batch_size(1024)
1223            .build(Cursor::new(buf.as_bytes()))
1224            .unwrap()
1225            .read()
1226            .unwrap_err();
1227
1228        assert_eq!(
1229            err.to_string(),
1230            "Json error: whilst decoding field 'a': expected string got 1"
1231        );
1232
1233        let buf = r#"{"a": true}"#;
1234        let err = ReaderBuilder::new(schema)
1235            .with_batch_size(1024)
1236            .build(Cursor::new(buf.as_bytes()))
1237            .unwrap()
1238            .read()
1239            .unwrap_err();
1240
1241        assert_eq!(
1242            err.to_string(),
1243            "Json error: whilst decoding field 'a': expected string got true"
1244        );
1245    }
1246
1247    #[test]
1248    fn test_coercing_primitive_into_string() {
1249        let buf = r#"
1250        {"a": 1, "b": 2, "c": true}
1251        {"a": 2E0, "b": 4, "c": false}
1252
1253        {"b": 6, "a": 2.0}
1254        {"b": "5", "a": 2}
1255        {"b": 4e0}
1256        {"b": 7, "a": null}
1257        "#;
1258
1259        let schema = Arc::new(Schema::new(vec![
1260            Field::new("a", DataType::Utf8, true),
1261            Field::new("b", DataType::Utf8, true),
1262            Field::new("c", DataType::Utf8, true),
1263        ]));
1264
1265        let batches = do_read(buf, 1024, true, false, schema);
1266        assert_eq!(batches.len(), 1);
1267
1268        let col1 = batches[0].column(0).as_string::<i32>();
1269        assert_eq!(col1.null_count(), 2);
1270        assert_eq!(col1.value(0), "1");
1271        assert_eq!(col1.value(1), "2E0");
1272        assert_eq!(col1.value(2), "2.0");
1273        assert_eq!(col1.value(3), "2");
1274        assert!(col1.is_null(4));
1275        assert!(col1.is_null(5));
1276
1277        let col2 = batches[0].column(1).as_string::<i32>();
1278        assert_eq!(col2.null_count(), 0);
1279        assert_eq!(col2.value(0), "2");
1280        assert_eq!(col2.value(1), "4");
1281        assert_eq!(col2.value(2), "6");
1282        assert_eq!(col2.value(3), "5");
1283        assert_eq!(col2.value(4), "4e0");
1284        assert_eq!(col2.value(5), "7");
1285
1286        let col3 = batches[0].column(2).as_string::<i32>();
1287        assert_eq!(col3.null_count(), 4);
1288        assert_eq!(col3.value(0), "true");
1289        assert_eq!(col3.value(1), "false");
1290        assert!(col3.is_null(2));
1291        assert!(col3.is_null(3));
1292        assert!(col3.is_null(4));
1293        assert!(col3.is_null(5));
1294    }
1295
1296    fn test_decimal<T: DecimalType>(data_type: DataType) {
1297        let buf = r#"
1298        {"a": 1, "b": 2, "c": 38.30}
1299        {"a": 2, "b": 4, "c": 123.456}
1300
1301        {"b": 1337, "a": "2.0452"}
1302        {"b": "5", "a": "11034.2"}
1303        {"b": 40}
1304        {"b": 1234, "a": null}
1305        "#;
1306
1307        let schema = Arc::new(Schema::new(vec![
1308            Field::new("a", data_type.clone(), true),
1309            Field::new("b", data_type.clone(), true),
1310            Field::new("c", data_type, true),
1311        ]));
1312
1313        let batches = do_read(buf, 1024, true, false, schema);
1314        assert_eq!(batches.len(), 1);
1315
1316        let col1 = batches[0].column(0).as_primitive::<T>();
1317        assert_eq!(col1.null_count(), 2);
1318        assert!(col1.is_null(4));
1319        assert!(col1.is_null(5));
1320        assert_eq!(
1321            col1.values(),
1322            &[100, 200, 204, 1103420, 0, 0].map(T::Native::usize_as)
1323        );
1324
1325        let col2 = batches[0].column(1).as_primitive::<T>();
1326        assert_eq!(col2.null_count(), 0);
1327        assert_eq!(
1328            col2.values(),
1329            &[200, 400, 133700, 500, 4000, 123400].map(T::Native::usize_as)
1330        );
1331
1332        let col3 = batches[0].column(2).as_primitive::<T>();
1333        assert_eq!(col3.null_count(), 4);
1334        assert!(!col3.is_null(0));
1335        assert!(!col3.is_null(1));
1336        assert!(col3.is_null(2));
1337        assert!(col3.is_null(3));
1338        assert!(col3.is_null(4));
1339        assert!(col3.is_null(5));
1340        assert_eq!(
1341            col3.values(),
1342            &[3830, 12345, 0, 0, 0, 0].map(T::Native::usize_as)
1343        );
1344    }
1345
1346    #[test]
1347    fn test_decimals() {
1348        test_decimal::<Decimal128Type>(DataType::Decimal128(10, 2));
1349        test_decimal::<Decimal256Type>(DataType::Decimal256(10, 2));
1350    }
1351
1352    fn test_timestamp<T: ArrowTimestampType>() {
1353        let buf = r#"
1354        {"a": 1, "b": "2020-09-08T13:42:29.190855+00:00", "c": 38.30, "d": "1997-01-31T09:26:56.123"}
1355        {"a": 2, "b": "2020-09-08T13:42:29.190855Z", "c": 123.456, "d": 123.456}
1356
1357        {"b": 1337, "b": "2020-09-08T13:42:29Z", "c": "1997-01-31T09:26:56.123", "d": "1997-01-31T09:26:56.123Z"}
1358        {"b": 40, "c": "2020-09-08T13:42:29.190855+00:00", "d": "1997-01-31 09:26:56.123-05:00"}
1359        {"b": 1234, "a": null, "c": "1997-01-31 09:26:56.123Z", "d": "1997-01-31 092656"}
1360        {"c": "1997-01-31T14:26:56.123-05:00", "d": "1997-01-31"}
1361        "#;
1362
1363        let with_timezone = DataType::Timestamp(T::UNIT, Some("+08:00".into()));
1364        let schema = Arc::new(Schema::new(vec![
1365            Field::new("a", T::DATA_TYPE, true),
1366            Field::new("b", T::DATA_TYPE, true),
1367            Field::new("c", T::DATA_TYPE, true),
1368            Field::new("d", with_timezone, true),
1369        ]));
1370
1371        let batches = do_read(buf, 1024, true, false, schema);
1372        assert_eq!(batches.len(), 1);
1373
1374        let unit_in_nanos: i64 = match T::UNIT {
1375            TimeUnit::Second => 1_000_000_000,
1376            TimeUnit::Millisecond => 1_000_000,
1377            TimeUnit::Microsecond => 1_000,
1378            TimeUnit::Nanosecond => 1,
1379        };
1380
1381        let col1 = batches[0].column(0).as_primitive::<T>();
1382        assert_eq!(col1.null_count(), 4);
1383        assert!(col1.is_null(2));
1384        assert!(col1.is_null(3));
1385        assert!(col1.is_null(4));
1386        assert!(col1.is_null(5));
1387        assert_eq!(col1.values(), &[1, 2, 0, 0, 0, 0].map(T::Native::usize_as));
1388
1389        let col2 = batches[0].column(1).as_primitive::<T>();
1390        assert_eq!(col2.null_count(), 1);
1391        assert!(col2.is_null(5));
1392        assert_eq!(
1393            col2.values(),
1394            &[
1395                1599572549190855000 / unit_in_nanos,
1396                1599572549190855000 / unit_in_nanos,
1397                1599572549000000000 / unit_in_nanos,
1398                40,
1399                1234,
1400                0
1401            ]
1402        );
1403
1404        let col3 = batches[0].column(2).as_primitive::<T>();
1405        assert_eq!(col3.null_count(), 0);
1406        assert_eq!(
1407            col3.values(),
1408            &[
1409                38,
1410                123,
1411                854702816123000000 / unit_in_nanos,
1412                1599572549190855000 / unit_in_nanos,
1413                854702816123000000 / unit_in_nanos,
1414                854738816123000000 / unit_in_nanos
1415            ]
1416        );
1417
1418        let col4 = batches[0].column(3).as_primitive::<T>();
1419
1420        assert_eq!(col4.null_count(), 0);
1421        assert_eq!(
1422            col4.values(),
1423            &[
1424                854674016123000000 / unit_in_nanos,
1425                123,
1426                854702816123000000 / unit_in_nanos,
1427                854720816123000000 / unit_in_nanos,
1428                854674016000000000 / unit_in_nanos,
1429                854640000000000000 / unit_in_nanos
1430            ]
1431        );
1432    }
1433
1434    #[test]
1435    fn test_timestamps() {
1436        test_timestamp::<TimestampSecondType>();
1437        test_timestamp::<TimestampMillisecondType>();
1438        test_timestamp::<TimestampMicrosecondType>();
1439        test_timestamp::<TimestampNanosecondType>();
1440    }
1441
1442    fn test_time<T: ArrowTemporalType>() {
1443        let buf = r#"
1444        {"a": 1, "b": "09:26:56.123 AM", "c": 38.30}
1445        {"a": 2, "b": "23:59:59", "c": 123.456}
1446
1447        {"b": 1337, "b": "6:00 pm", "c": "09:26:56.123"}
1448        {"b": 40, "c": "13:42:29.190855"}
1449        {"b": 1234, "a": null, "c": "09:26:56.123"}
1450        {"c": "14:26:56.123"}
1451        "#;
1452
1453        let unit = match T::DATA_TYPE {
1454            DataType::Time32(unit) | DataType::Time64(unit) => unit,
1455            _ => unreachable!(),
1456        };
1457
1458        let unit_in_nanos = match unit {
1459            TimeUnit::Second => 1_000_000_000,
1460            TimeUnit::Millisecond => 1_000_000,
1461            TimeUnit::Microsecond => 1_000,
1462            TimeUnit::Nanosecond => 1,
1463        };
1464
1465        let schema = Arc::new(Schema::new(vec![
1466            Field::new("a", T::DATA_TYPE, true),
1467            Field::new("b", T::DATA_TYPE, true),
1468            Field::new("c", T::DATA_TYPE, true),
1469        ]));
1470
1471        let batches = do_read(buf, 1024, true, false, schema);
1472        assert_eq!(batches.len(), 1);
1473
1474        let col1 = batches[0].column(0).as_primitive::<T>();
1475        assert_eq!(col1.null_count(), 4);
1476        assert!(col1.is_null(2));
1477        assert!(col1.is_null(3));
1478        assert!(col1.is_null(4));
1479        assert!(col1.is_null(5));
1480        assert_eq!(col1.values(), &[1, 2, 0, 0, 0, 0].map(T::Native::usize_as));
1481
1482        let col2 = batches[0].column(1).as_primitive::<T>();
1483        assert_eq!(col2.null_count(), 1);
1484        assert!(col2.is_null(5));
1485        assert_eq!(
1486            col2.values(),
1487            &[
1488                34016123000000 / unit_in_nanos,
1489                86399000000000 / unit_in_nanos,
1490                64800000000000 / unit_in_nanos,
1491                40,
1492                1234,
1493                0
1494            ]
1495            .map(T::Native::usize_as)
1496        );
1497
1498        let col3 = batches[0].column(2).as_primitive::<T>();
1499        assert_eq!(col3.null_count(), 0);
1500        assert_eq!(
1501            col3.values(),
1502            &[
1503                38,
1504                123,
1505                34016123000000 / unit_in_nanos,
1506                49349190855000 / unit_in_nanos,
1507                34016123000000 / unit_in_nanos,
1508                52016123000000 / unit_in_nanos
1509            ]
1510            .map(T::Native::usize_as)
1511        );
1512    }
1513
1514    #[test]
1515    fn test_times() {
1516        test_time::<Time32MillisecondType>();
1517        test_time::<Time32SecondType>();
1518        test_time::<Time64MicrosecondType>();
1519        test_time::<Time64NanosecondType>();
1520    }
1521
1522    fn test_duration<T: ArrowTemporalType>() {
1523        let buf = r#"
1524        {"a": 1, "b": "2"}
1525        {"a": 3, "b": null}
1526        "#;
1527
1528        let schema = Arc::new(Schema::new(vec![
1529            Field::new("a", T::DATA_TYPE, true),
1530            Field::new("b", T::DATA_TYPE, true),
1531        ]));
1532
1533        let batches = do_read(buf, 1024, true, false, schema);
1534        assert_eq!(batches.len(), 1);
1535
1536        let col_a = batches[0].column_by_name("a").unwrap().as_primitive::<T>();
1537        assert_eq!(col_a.null_count(), 0);
1538        assert_eq!(col_a.values(), &[1, 3].map(T::Native::usize_as));
1539
1540        let col2 = batches[0].column_by_name("b").unwrap().as_primitive::<T>();
1541        assert_eq!(col2.null_count(), 1);
1542        assert_eq!(col2.values(), &[2, 0].map(T::Native::usize_as));
1543    }
1544
1545    #[test]
1546    fn test_durations() {
1547        test_duration::<DurationNanosecondType>();
1548        test_duration::<DurationMicrosecondType>();
1549        test_duration::<DurationMillisecondType>();
1550        test_duration::<DurationSecondType>();
1551    }
1552
1553    #[test]
1554    fn test_delta_checkpoint() {
1555        let json = "{\"protocol\":{\"minReaderVersion\":1,\"minWriterVersion\":2}}";
1556        let schema = Arc::new(Schema::new(vec![
1557            Field::new_struct(
1558                "protocol",
1559                vec![
1560                    Field::new("minReaderVersion", DataType::Int32, true),
1561                    Field::new("minWriterVersion", DataType::Int32, true),
1562                ],
1563                true,
1564            ),
1565            Field::new_struct(
1566                "add",
1567                vec![Field::new_map(
1568                    "partitionValues",
1569                    "key_value",
1570                    Field::new("key", DataType::Utf8, false),
1571                    Field::new("value", DataType::Utf8, true),
1572                    false,
1573                    false,
1574                )],
1575                true,
1576            ),
1577        ]));
1578
1579        let batches = do_read(json, 1024, true, false, schema);
1580        assert_eq!(batches.len(), 1);
1581
1582        let s: StructArray = batches.into_iter().next().unwrap().into();
1583        let opts = FormatOptions::default().with_null("null");
1584        let formatter = ArrayFormatter::try_new(&s, &opts).unwrap();
1585        assert_eq!(
1586            formatter.value(0).to_string(),
1587            "{protocol: {minReaderVersion: 1, minWriterVersion: 2}, add: null}"
1588        );
1589    }
1590
1591    #[test]
1592    fn struct_nullability() {
1593        let do_test = |child: DataType| {
1594            // Test correctly enforced nullability
1595            let non_null = r#"{"foo": {}}"#;
1596            let schema = Arc::new(Schema::new(vec![Field::new_struct(
1597                "foo",
1598                vec![Field::new("bar", child, false)],
1599                true,
1600            )]));
1601            let mut reader = ReaderBuilder::new(schema.clone())
1602                .build(Cursor::new(non_null.as_bytes()))
1603                .unwrap();
1604            assert!(reader.next().unwrap().is_err()); // Should error as not nullable
1605
1606            let null = r#"{"foo": {bar: null}}"#;
1607            let mut reader = ReaderBuilder::new(schema.clone())
1608                .build(Cursor::new(null.as_bytes()))
1609                .unwrap();
1610            assert!(reader.next().unwrap().is_err()); // Should error as not nullable
1611
1612            // Test nulls in nullable parent can mask nulls in non-nullable child
1613            let null = r#"{"foo": null}"#;
1614            let mut reader = ReaderBuilder::new(schema)
1615                .build(Cursor::new(null.as_bytes()))
1616                .unwrap();
1617            let batch = reader.next().unwrap().unwrap();
1618            assert_eq!(batch.num_columns(), 1);
1619            let foo = batch.column(0).as_struct();
1620            assert_eq!(foo.len(), 1);
1621            assert!(foo.is_null(0));
1622            assert_eq!(foo.num_columns(), 1);
1623
1624            let bar = foo.column(0);
1625            assert_eq!(bar.len(), 1);
1626            // Non-nullable child can still contain null as masked by parent
1627            assert!(bar.is_null(0));
1628        };
1629
1630        do_test(DataType::Boolean);
1631        do_test(DataType::Int32);
1632        do_test(DataType::Utf8);
1633        do_test(DataType::Decimal128(2, 1));
1634        do_test(DataType::Timestamp(
1635            TimeUnit::Microsecond,
1636            Some("+00:00".into()),
1637        ));
1638    }
1639
1640    #[test]
1641    fn test_truncation() {
1642        let buf = r#"
1643        {"i64": 9223372036854775807, "u64": 18446744073709551615 }
1644        {"i64": "9223372036854775807", "u64": "18446744073709551615" }
1645        {"i64": -9223372036854775808, "u64": 0 }
1646        {"i64": "-9223372036854775808", "u64": 0 }
1647        "#;
1648
1649        let schema = Arc::new(Schema::new(vec![
1650            Field::new("i64", DataType::Int64, true),
1651            Field::new("u64", DataType::UInt64, true),
1652        ]));
1653
1654        let batches = do_read(buf, 1024, true, false, schema);
1655        assert_eq!(batches.len(), 1);
1656
1657        let i64 = batches[0].column(0).as_primitive::<Int64Type>();
1658        assert_eq!(i64.values(), &[i64::MAX, i64::MAX, i64::MIN, i64::MIN]);
1659
1660        let u64 = batches[0].column(1).as_primitive::<UInt64Type>();
1661        assert_eq!(u64.values(), &[u64::MAX, u64::MAX, u64::MIN, u64::MIN]);
1662    }
1663
1664    #[test]
1665    fn test_timestamp_truncation() {
1666        let buf = r#"
1667        {"time": 9223372036854775807 }
1668        {"time": -9223372036854775808 }
1669        {"time": 9e5 }
1670        "#;
1671
1672        let schema = Arc::new(Schema::new(vec![Field::new(
1673            "time",
1674            DataType::Timestamp(TimeUnit::Nanosecond, None),
1675            true,
1676        )]));
1677
1678        let batches = do_read(buf, 1024, true, false, schema);
1679        assert_eq!(batches.len(), 1);
1680
1681        let i64 = batches[0]
1682            .column(0)
1683            .as_primitive::<TimestampNanosecondType>();
1684        assert_eq!(i64.values(), &[i64::MAX, i64::MIN, 900000]);
1685    }
1686
1687    #[test]
1688    fn test_strict_mode_no_missing_columns_in_schema() {
1689        let buf = r#"
1690        {"a": 1, "b": "2", "c": true}
1691        {"a": 2E0, "b": "4", "c": false}
1692        "#;
1693
1694        let schema = Arc::new(Schema::new(vec![
1695            Field::new("a", DataType::Int16, false),
1696            Field::new("b", DataType::Utf8, false),
1697            Field::new("c", DataType::Boolean, false),
1698        ]));
1699
1700        let batches = do_read(buf, 1024, true, true, schema);
1701        assert_eq!(batches.len(), 1);
1702
1703        let buf = r#"
1704        {"a": 1, "b": "2", "c": {"a": true, "b": 1}}
1705        {"a": 2E0, "b": "4", "c": {"a": false, "b": 2}}
1706        "#;
1707
1708        let schema = Arc::new(Schema::new(vec![
1709            Field::new("a", DataType::Int16, false),
1710            Field::new("b", DataType::Utf8, false),
1711            Field::new_struct(
1712                "c",
1713                vec![
1714                    Field::new("a", DataType::Boolean, false),
1715                    Field::new("b", DataType::Int16, false),
1716                ],
1717                false,
1718            ),
1719        ]));
1720
1721        let batches = do_read(buf, 1024, true, true, schema);
1722        assert_eq!(batches.len(), 1);
1723    }
1724
1725    #[test]
1726    fn test_strict_mode_missing_columns_in_schema() {
1727        let buf = r#"
1728        {"a": 1, "b": "2", "c": true}
1729        {"a": 2E0, "b": "4", "c": false}
1730        "#;
1731
1732        let schema = Arc::new(Schema::new(vec![
1733            Field::new("a", DataType::Int16, true),
1734            Field::new("c", DataType::Boolean, true),
1735        ]));
1736
1737        let err = ReaderBuilder::new(schema)
1738            .with_batch_size(1024)
1739            .with_strict_mode(true)
1740            .build(Cursor::new(buf.as_bytes()))
1741            .unwrap()
1742            .read()
1743            .unwrap_err();
1744
1745        assert_eq!(
1746            err.to_string(),
1747            "Json error: column 'b' missing from schema"
1748        );
1749
1750        let buf = r#"
1751        {"a": 1, "b": "2", "c": {"a": true, "b": 1}}
1752        {"a": 2E0, "b": "4", "c": {"a": false, "b": 2}}
1753        "#;
1754
1755        let schema = Arc::new(Schema::new(vec![
1756            Field::new("a", DataType::Int16, false),
1757            Field::new("b", DataType::Utf8, false),
1758            Field::new_struct("c", vec![Field::new("a", DataType::Boolean, false)], false),
1759        ]));
1760
1761        let err = ReaderBuilder::new(schema)
1762            .with_batch_size(1024)
1763            .with_strict_mode(true)
1764            .build(Cursor::new(buf.as_bytes()))
1765            .unwrap()
1766            .read()
1767            .unwrap_err();
1768
1769        assert_eq!(
1770            err.to_string(),
1771            "Json error: whilst decoding field 'c': column 'b' missing from schema"
1772        );
1773    }
1774
1775    fn read_file(path: &str, schema: Option<Schema>) -> Reader<BufReader<File>> {
1776        let file = File::open(path).unwrap();
1777        let mut reader = BufReader::new(file);
1778        let schema = schema.unwrap_or_else(|| {
1779            let (schema, _) = infer_json_schema(&mut reader, None).unwrap();
1780            reader.rewind().unwrap();
1781            schema
1782        });
1783        let builder = ReaderBuilder::new(Arc::new(schema)).with_batch_size(64);
1784        builder.build(reader).unwrap()
1785    }
1786
1787    #[test]
1788    fn test_json_basic() {
1789        let mut reader = read_file("test/data/basic.json", None);
1790        let batch = reader.next().unwrap().unwrap();
1791
1792        assert_eq!(8, batch.num_columns());
1793        assert_eq!(12, batch.num_rows());
1794
1795        let schema = reader.schema();
1796        let batch_schema = batch.schema();
1797        assert_eq!(schema, batch_schema);
1798
1799        let a = schema.column_with_name("a").unwrap();
1800        assert_eq!(0, a.0);
1801        assert_eq!(&DataType::Int64, a.1.data_type());
1802        let b = schema.column_with_name("b").unwrap();
1803        assert_eq!(1, b.0);
1804        assert_eq!(&DataType::Float64, b.1.data_type());
1805        let c = schema.column_with_name("c").unwrap();
1806        assert_eq!(2, c.0);
1807        assert_eq!(&DataType::Boolean, c.1.data_type());
1808        let d = schema.column_with_name("d").unwrap();
1809        assert_eq!(3, d.0);
1810        assert_eq!(&DataType::Utf8, d.1.data_type());
1811
1812        let aa = batch.column(a.0).as_primitive::<Int64Type>();
1813        assert_eq!(1, aa.value(0));
1814        assert_eq!(-10, aa.value(1));
1815        let bb = batch.column(b.0).as_primitive::<Float64Type>();
1816        assert_eq!(2.0, bb.value(0));
1817        assert_eq!(-3.5, bb.value(1));
1818        let cc = batch.column(c.0).as_boolean();
1819        assert!(!cc.value(0));
1820        assert!(cc.value(10));
1821        let dd = batch.column(d.0).as_string::<i32>();
1822        assert_eq!("4", dd.value(0));
1823        assert_eq!("text", dd.value(8));
1824    }
1825
1826    #[test]
1827    fn test_json_empty_projection() {
1828        let mut reader = read_file("test/data/basic.json", Some(Schema::empty()));
1829        let batch = reader.next().unwrap().unwrap();
1830
1831        assert_eq!(0, batch.num_columns());
1832        assert_eq!(12, batch.num_rows());
1833    }
1834
1835    #[test]
1836    fn test_json_basic_with_nulls() {
1837        let mut reader = read_file("test/data/basic_nulls.json", None);
1838        let batch = reader.next().unwrap().unwrap();
1839
1840        assert_eq!(4, batch.num_columns());
1841        assert_eq!(12, batch.num_rows());
1842
1843        let schema = reader.schema();
1844        let batch_schema = batch.schema();
1845        assert_eq!(schema, batch_schema);
1846
1847        let a = schema.column_with_name("a").unwrap();
1848        assert_eq!(&DataType::Int64, a.1.data_type());
1849        let b = schema.column_with_name("b").unwrap();
1850        assert_eq!(&DataType::Float64, b.1.data_type());
1851        let c = schema.column_with_name("c").unwrap();
1852        assert_eq!(&DataType::Boolean, c.1.data_type());
1853        let d = schema.column_with_name("d").unwrap();
1854        assert_eq!(&DataType::Utf8, d.1.data_type());
1855
1856        let aa = batch.column(a.0).as_primitive::<Int64Type>();
1857        assert!(aa.is_valid(0));
1858        assert!(!aa.is_valid(1));
1859        assert!(!aa.is_valid(11));
1860        let bb = batch.column(b.0).as_primitive::<Float64Type>();
1861        assert!(bb.is_valid(0));
1862        assert!(!bb.is_valid(2));
1863        assert!(!bb.is_valid(11));
1864        let cc = batch.column(c.0).as_boolean();
1865        assert!(cc.is_valid(0));
1866        assert!(!cc.is_valid(4));
1867        assert!(!cc.is_valid(11));
1868        let dd = batch.column(d.0).as_string::<i32>();
1869        assert!(!dd.is_valid(0));
1870        assert!(dd.is_valid(1));
1871        assert!(!dd.is_valid(4));
1872        assert!(!dd.is_valid(11));
1873    }
1874
1875    #[test]
1876    fn test_json_basic_schema() {
1877        let schema = Schema::new(vec![
1878            Field::new("a", DataType::Int64, true),
1879            Field::new("b", DataType::Float32, false),
1880            Field::new("c", DataType::Boolean, false),
1881            Field::new("d", DataType::Utf8, false),
1882        ]);
1883
1884        let mut reader = read_file("test/data/basic.json", Some(schema.clone()));
1885        let reader_schema = reader.schema();
1886        assert_eq!(reader_schema.as_ref(), &schema);
1887        let batch = reader.next().unwrap().unwrap();
1888
1889        assert_eq!(4, batch.num_columns());
1890        assert_eq!(12, batch.num_rows());
1891
1892        let schema = batch.schema();
1893
1894        let a = schema.column_with_name("a").unwrap();
1895        assert_eq!(&DataType::Int64, a.1.data_type());
1896        let b = schema.column_with_name("b").unwrap();
1897        assert_eq!(&DataType::Float32, b.1.data_type());
1898        let c = schema.column_with_name("c").unwrap();
1899        assert_eq!(&DataType::Boolean, c.1.data_type());
1900        let d = schema.column_with_name("d").unwrap();
1901        assert_eq!(&DataType::Utf8, d.1.data_type());
1902
1903        let aa = batch.column(a.0).as_primitive::<Int64Type>();
1904        assert_eq!(1, aa.value(0));
1905        assert_eq!(100000000000000, aa.value(11));
1906        let bb = batch.column(b.0).as_primitive::<Float32Type>();
1907        assert_eq!(2.0, bb.value(0));
1908        assert_eq!(-3.5, bb.value(1));
1909    }
1910
1911    #[test]
1912    fn test_json_basic_schema_projection() {
1913        let schema = Schema::new(vec![
1914            Field::new("a", DataType::Int64, true),
1915            Field::new("c", DataType::Boolean, false),
1916        ]);
1917
1918        let mut reader = read_file("test/data/basic.json", Some(schema.clone()));
1919        let batch = reader.next().unwrap().unwrap();
1920
1921        assert_eq!(2, batch.num_columns());
1922        assert_eq!(2, batch.schema().fields().len());
1923        assert_eq!(12, batch.num_rows());
1924
1925        assert_eq!(batch.schema().as_ref(), &schema);
1926
1927        let a = schema.column_with_name("a").unwrap();
1928        assert_eq!(0, a.0);
1929        assert_eq!(&DataType::Int64, a.1.data_type());
1930        let c = schema.column_with_name("c").unwrap();
1931        assert_eq!(1, c.0);
1932        assert_eq!(&DataType::Boolean, c.1.data_type());
1933    }
1934
1935    #[test]
1936    fn test_json_arrays() {
1937        let mut reader = read_file("test/data/arrays.json", None);
1938        let batch = reader.next().unwrap().unwrap();
1939
1940        assert_eq!(4, batch.num_columns());
1941        assert_eq!(3, batch.num_rows());
1942
1943        let schema = batch.schema();
1944
1945        let a = schema.column_with_name("a").unwrap();
1946        assert_eq!(&DataType::Int64, a.1.data_type());
1947        let b = schema.column_with_name("b").unwrap();
1948        assert_eq!(
1949            &DataType::List(Arc::new(Field::new_list_field(DataType::Float64, true))),
1950            b.1.data_type()
1951        );
1952        let c = schema.column_with_name("c").unwrap();
1953        assert_eq!(
1954            &DataType::List(Arc::new(Field::new_list_field(DataType::Boolean, true))),
1955            c.1.data_type()
1956        );
1957        let d = schema.column_with_name("d").unwrap();
1958        assert_eq!(&DataType::Utf8, d.1.data_type());
1959
1960        let aa = batch.column(a.0).as_primitive::<Int64Type>();
1961        assert_eq!(1, aa.value(0));
1962        assert_eq!(-10, aa.value(1));
1963        assert_eq!(1627668684594000000, aa.value(2));
1964        let bb = batch.column(b.0).as_list::<i32>();
1965        let bb = bb.values().as_primitive::<Float64Type>();
1966        assert_eq!(9, bb.len());
1967        assert_eq!(2.0, bb.value(0));
1968        assert_eq!(-6.1, bb.value(5));
1969        assert!(!bb.is_valid(7));
1970
1971        let cc = batch
1972            .column(c.0)
1973            .as_any()
1974            .downcast_ref::<ListArray>()
1975            .unwrap();
1976        let cc = cc.values().as_boolean();
1977        assert_eq!(6, cc.len());
1978        assert!(!cc.value(0));
1979        assert!(!cc.value(4));
1980        assert!(!cc.is_valid(5));
1981    }
1982
1983    #[test]
1984    fn test_empty_json_arrays() {
1985        let json_content = r#"
1986            {"items": []}
1987            {"items": null}
1988            {}
1989            "#;
1990
1991        let schema = Arc::new(Schema::new(vec![Field::new(
1992            "items",
1993            DataType::List(FieldRef::new(Field::new_list_field(DataType::Null, true))),
1994            true,
1995        )]));
1996
1997        let batches = do_read(json_content, 1024, false, false, schema);
1998        assert_eq!(batches.len(), 1);
1999
2000        let col1 = batches[0].column(0).as_list::<i32>();
2001        assert_eq!(col1.null_count(), 2);
2002        assert!(col1.value(0).is_empty());
2003        assert_eq!(col1.value(0).data_type(), &DataType::Null);
2004        assert!(col1.is_null(1));
2005        assert!(col1.is_null(2));
2006    }
2007
2008    #[test]
2009    fn test_nested_empty_json_arrays() {
2010        let json_content = r#"
2011            {"items": [[],[]]}
2012            {"items": [[null, null],[null]]}
2013            "#;
2014
2015        let schema = Arc::new(Schema::new(vec![Field::new(
2016            "items",
2017            DataType::List(FieldRef::new(Field::new_list_field(
2018                DataType::List(FieldRef::new(Field::new_list_field(DataType::Null, true))),
2019                true,
2020            ))),
2021            true,
2022        )]));
2023
2024        let batches = do_read(json_content, 1024, false, false, schema);
2025        assert_eq!(batches.len(), 1);
2026
2027        let col1 = batches[0].column(0).as_list::<i32>();
2028        assert_eq!(col1.null_count(), 0);
2029        assert_eq!(col1.value(0).len(), 2);
2030        assert!(col1.value(0).as_list::<i32>().value(0).is_empty());
2031        assert!(col1.value(0).as_list::<i32>().value(1).is_empty());
2032
2033        assert_eq!(col1.value(1).len(), 2);
2034        assert_eq!(col1.value(1).as_list::<i32>().value(0).len(), 2);
2035        assert_eq!(col1.value(1).as_list::<i32>().value(1).len(), 1);
2036    }
2037
2038    #[test]
2039    fn test_nested_list_json_arrays() {
2040        let c_field = Field::new_struct("c", vec![Field::new("d", DataType::Utf8, true)], true);
2041        let a_struct_field = Field::new_struct(
2042            "a",
2043            vec![Field::new("b", DataType::Boolean, true), c_field.clone()],
2044            true,
2045        );
2046        let a_field = Field::new("a", DataType::List(Arc::new(a_struct_field.clone())), true);
2047        let schema = Arc::new(Schema::new(vec![a_field.clone()]));
2048        let builder = ReaderBuilder::new(schema).with_batch_size(64);
2049        let json_content = r#"
2050        {"a": [{"b": true, "c": {"d": "a_text"}}, {"b": false, "c": {"d": "b_text"}}]}
2051        {"a": [{"b": false, "c": null}]}
2052        {"a": [{"b": true, "c": {"d": "c_text"}}, {"b": null, "c": {"d": "d_text"}}, {"b": true, "c": {"d": null}}]}
2053        {"a": null}
2054        {"a": []}
2055        {"a": [null]}
2056        "#;
2057        let mut reader = builder.build(Cursor::new(json_content)).unwrap();
2058
2059        // build expected output
2060        let d = StringArray::from(vec![
2061            Some("a_text"),
2062            Some("b_text"),
2063            None,
2064            Some("c_text"),
2065            Some("d_text"),
2066            None,
2067            None,
2068        ]);
2069        let c = ArrayDataBuilder::new(c_field.data_type().clone())
2070            .len(7)
2071            .add_child_data(d.to_data())
2072            .null_bit_buffer(Some(Buffer::from([0b00111011])))
2073            .build()
2074            .unwrap();
2075        let b = BooleanArray::from(vec![
2076            Some(true),
2077            Some(false),
2078            Some(false),
2079            Some(true),
2080            None,
2081            Some(true),
2082            None,
2083        ]);
2084        let a = ArrayDataBuilder::new(a_struct_field.data_type().clone())
2085            .len(7)
2086            .add_child_data(b.to_data())
2087            .add_child_data(c.clone())
2088            .null_bit_buffer(Some(Buffer::from([0b00111111])))
2089            .build()
2090            .unwrap();
2091        let a_list = ArrayDataBuilder::new(a_field.data_type().clone())
2092            .len(6)
2093            .add_buffer(Buffer::from_slice_ref([0i32, 2, 3, 6, 6, 6, 7]))
2094            .add_child_data(a)
2095            .null_bit_buffer(Some(Buffer::from([0b00110111])))
2096            .build()
2097            .unwrap();
2098        let expected = make_array(a_list);
2099
2100        // compare `a` with result from json reader
2101        let batch = reader.next().unwrap().unwrap();
2102        let read = batch.column(0);
2103        assert_eq!(read.len(), 6);
2104        // compare the arrays the long way around, to better detect differences
2105        let read: &ListArray = read.as_list::<i32>();
2106        let expected = expected.as_list::<i32>();
2107        assert_eq!(read.value_offsets(), &[0, 2, 3, 6, 6, 6, 7]);
2108        // compare list null buffers
2109        assert_eq!(read.nulls(), expected.nulls());
2110        // build struct from list
2111        let struct_array = read.values().as_struct();
2112        let expected_struct_array = expected.values().as_struct();
2113
2114        assert_eq!(7, struct_array.len());
2115        assert_eq!(1, struct_array.null_count());
2116        assert_eq!(7, expected_struct_array.len());
2117        assert_eq!(1, expected_struct_array.null_count());
2118        // test struct's nulls
2119        assert_eq!(struct_array.nulls(), expected_struct_array.nulls());
2120        // test struct's fields
2121        let read_b = struct_array.column(0);
2122        assert_eq!(read_b.as_ref(), &b);
2123        let read_c = struct_array.column(1);
2124        assert_eq!(read_c.to_data(), c);
2125        let read_c = read_c.as_struct();
2126        let read_d = read_c.column(0);
2127        assert_eq!(read_d.as_ref(), &d);
2128
2129        assert_eq!(read, expected);
2130    }
2131
2132    #[test]
2133    fn test_skip_empty_lines() {
2134        let schema = Schema::new(vec![Field::new("a", DataType::Int64, true)]);
2135        let builder = ReaderBuilder::new(Arc::new(schema)).with_batch_size(64);
2136        let json_content = "
2137        {\"a\": 1}
2138        {\"a\": 2}
2139        {\"a\": 3}";
2140        let mut reader = builder.build(Cursor::new(json_content)).unwrap();
2141        let batch = reader.next().unwrap().unwrap();
2142
2143        assert_eq!(1, batch.num_columns());
2144        assert_eq!(3, batch.num_rows());
2145
2146        let schema = reader.schema();
2147        let c = schema.column_with_name("a").unwrap();
2148        assert_eq!(&DataType::Int64, c.1.data_type());
2149    }
2150
2151    #[test]
2152    fn test_with_multiple_batches() {
2153        let file = File::open("test/data/basic_nulls.json").unwrap();
2154        let mut reader = BufReader::new(file);
2155        let (schema, _) = infer_json_schema(&mut reader, None).unwrap();
2156        reader.rewind().unwrap();
2157
2158        let builder = ReaderBuilder::new(Arc::new(schema)).with_batch_size(5);
2159        let mut reader = builder.build(reader).unwrap();
2160
2161        let mut num_records = Vec::new();
2162        while let Some(rb) = reader.next().transpose().unwrap() {
2163            num_records.push(rb.num_rows());
2164        }
2165
2166        assert_eq!(vec![5, 5, 2], num_records);
2167    }
2168
2169    #[test]
2170    fn test_timestamp_from_json_seconds() {
2171        let schema = Schema::new(vec![Field::new(
2172            "a",
2173            DataType::Timestamp(TimeUnit::Second, None),
2174            true,
2175        )]);
2176
2177        let mut reader = read_file("test/data/basic_nulls.json", Some(schema));
2178        let batch = reader.next().unwrap().unwrap();
2179
2180        assert_eq!(1, batch.num_columns());
2181        assert_eq!(12, batch.num_rows());
2182
2183        let schema = reader.schema();
2184        let batch_schema = batch.schema();
2185        assert_eq!(schema, batch_schema);
2186
2187        let a = schema.column_with_name("a").unwrap();
2188        assert_eq!(
2189            &DataType::Timestamp(TimeUnit::Second, None),
2190            a.1.data_type()
2191        );
2192
2193        let aa = batch.column(a.0).as_primitive::<TimestampSecondType>();
2194        assert!(aa.is_valid(0));
2195        assert!(!aa.is_valid(1));
2196        assert!(!aa.is_valid(2));
2197        assert_eq!(1, aa.value(0));
2198        assert_eq!(1, aa.value(3));
2199        assert_eq!(5, aa.value(7));
2200    }
2201
2202    #[test]
2203    fn test_timestamp_from_json_milliseconds() {
2204        let schema = Schema::new(vec![Field::new(
2205            "a",
2206            DataType::Timestamp(TimeUnit::Millisecond, None),
2207            true,
2208        )]);
2209
2210        let mut reader = read_file("test/data/basic_nulls.json", Some(schema));
2211        let batch = reader.next().unwrap().unwrap();
2212
2213        assert_eq!(1, batch.num_columns());
2214        assert_eq!(12, batch.num_rows());
2215
2216        let schema = reader.schema();
2217        let batch_schema = batch.schema();
2218        assert_eq!(schema, batch_schema);
2219
2220        let a = schema.column_with_name("a").unwrap();
2221        assert_eq!(
2222            &DataType::Timestamp(TimeUnit::Millisecond, None),
2223            a.1.data_type()
2224        );
2225
2226        let aa = batch.column(a.0).as_primitive::<TimestampMillisecondType>();
2227        assert!(aa.is_valid(0));
2228        assert!(!aa.is_valid(1));
2229        assert!(!aa.is_valid(2));
2230        assert_eq!(1, aa.value(0));
2231        assert_eq!(1, aa.value(3));
2232        assert_eq!(5, aa.value(7));
2233    }
2234
2235    #[test]
2236    fn test_date_from_json_milliseconds() {
2237        let schema = Schema::new(vec![Field::new("a", DataType::Date64, true)]);
2238
2239        let mut reader = read_file("test/data/basic_nulls.json", Some(schema));
2240        let batch = reader.next().unwrap().unwrap();
2241
2242        assert_eq!(1, batch.num_columns());
2243        assert_eq!(12, batch.num_rows());
2244
2245        let schema = reader.schema();
2246        let batch_schema = batch.schema();
2247        assert_eq!(schema, batch_schema);
2248
2249        let a = schema.column_with_name("a").unwrap();
2250        assert_eq!(&DataType::Date64, a.1.data_type());
2251
2252        let aa = batch.column(a.0).as_primitive::<Date64Type>();
2253        assert!(aa.is_valid(0));
2254        assert!(!aa.is_valid(1));
2255        assert!(!aa.is_valid(2));
2256        assert_eq!(1, aa.value(0));
2257        assert_eq!(1, aa.value(3));
2258        assert_eq!(5, aa.value(7));
2259    }
2260
2261    #[test]
2262    fn test_time_from_json_nanoseconds() {
2263        let schema = Schema::new(vec![Field::new(
2264            "a",
2265            DataType::Time64(TimeUnit::Nanosecond),
2266            true,
2267        )]);
2268
2269        let mut reader = read_file("test/data/basic_nulls.json", Some(schema));
2270        let batch = reader.next().unwrap().unwrap();
2271
2272        assert_eq!(1, batch.num_columns());
2273        assert_eq!(12, batch.num_rows());
2274
2275        let schema = reader.schema();
2276        let batch_schema = batch.schema();
2277        assert_eq!(schema, batch_schema);
2278
2279        let a = schema.column_with_name("a").unwrap();
2280        assert_eq!(&DataType::Time64(TimeUnit::Nanosecond), a.1.data_type());
2281
2282        let aa = batch.column(a.0).as_primitive::<Time64NanosecondType>();
2283        assert!(aa.is_valid(0));
2284        assert!(!aa.is_valid(1));
2285        assert!(!aa.is_valid(2));
2286        assert_eq!(1, aa.value(0));
2287        assert_eq!(1, aa.value(3));
2288        assert_eq!(5, aa.value(7));
2289    }
2290
2291    #[test]
2292    fn test_json_iterator() {
2293        let file = File::open("test/data/basic.json").unwrap();
2294        let mut reader = BufReader::new(file);
2295        let (schema, _) = infer_json_schema(&mut reader, None).unwrap();
2296        reader.rewind().unwrap();
2297
2298        let builder = ReaderBuilder::new(Arc::new(schema)).with_batch_size(5);
2299        let reader = builder.build(reader).unwrap();
2300        let schema = reader.schema();
2301        let (col_a_index, _) = schema.column_with_name("a").unwrap();
2302
2303        let mut sum_num_rows = 0;
2304        let mut num_batches = 0;
2305        let mut sum_a = 0;
2306        for batch in reader {
2307            let batch = batch.unwrap();
2308            assert_eq!(8, batch.num_columns());
2309            sum_num_rows += batch.num_rows();
2310            num_batches += 1;
2311            let batch_schema = batch.schema();
2312            assert_eq!(schema, batch_schema);
2313            let a_array = batch.column(col_a_index).as_primitive::<Int64Type>();
2314            sum_a += (0..a_array.len()).map(|i| a_array.value(i)).sum::<i64>();
2315        }
2316        assert_eq!(12, sum_num_rows);
2317        assert_eq!(3, num_batches);
2318        assert_eq!(100000000000011, sum_a);
2319    }
2320
2321    #[test]
2322    fn test_decoder_error() {
2323        let schema = Arc::new(Schema::new(vec![Field::new_struct(
2324            "a",
2325            vec![Field::new("child", DataType::Int32, false)],
2326            true,
2327        )]));
2328
2329        let mut decoder = ReaderBuilder::new(schema.clone()).build_decoder().unwrap();
2330        let _ = decoder.decode(r#"{"a": { "child":"#.as_bytes()).unwrap();
2331        assert!(decoder.tape_decoder.has_partial_row());
2332        assert_eq!(decoder.tape_decoder.num_buffered_rows(), 1);
2333        let _ = decoder.flush().unwrap_err();
2334        assert!(decoder.tape_decoder.has_partial_row());
2335        assert_eq!(decoder.tape_decoder.num_buffered_rows(), 1);
2336
2337        let parse_err = |s: &str| {
2338            ReaderBuilder::new(schema.clone())
2339                .build(Cursor::new(s.as_bytes()))
2340                .unwrap()
2341                .next()
2342                .unwrap()
2343                .unwrap_err()
2344                .to_string()
2345        };
2346
2347        let err = parse_err(r#"{"a": 123}"#);
2348        assert_eq!(
2349            err,
2350            "Json error: whilst decoding field 'a': expected { got 123"
2351        );
2352
2353        let err = parse_err(r#"{"a": ["bar"]}"#);
2354        assert_eq!(
2355            err,
2356            r#"Json error: whilst decoding field 'a': expected { got ["bar"]"#
2357        );
2358
2359        let err = parse_err(r#"{"a": []}"#);
2360        assert_eq!(
2361            err,
2362            "Json error: whilst decoding field 'a': expected { got []"
2363        );
2364
2365        let err = parse_err(r#"{"a": [{"child": 234}]}"#);
2366        assert_eq!(
2367            err,
2368            r#"Json error: whilst decoding field 'a': expected { got [{"child": 234}]"#
2369        );
2370
2371        let err = parse_err(r#"{"a": [{"child": {"foo": [{"foo": ["bar"]}]}}]}"#);
2372        assert_eq!(
2373            err,
2374            r#"Json error: whilst decoding field 'a': expected { got [{"child": {"foo": [{"foo": ["bar"]}]}}]"#
2375        );
2376
2377        let err = parse_err(r#"{"a": true}"#);
2378        assert_eq!(
2379            err,
2380            "Json error: whilst decoding field 'a': expected { got true"
2381        );
2382
2383        let err = parse_err(r#"{"a": false}"#);
2384        assert_eq!(
2385            err,
2386            "Json error: whilst decoding field 'a': expected { got false"
2387        );
2388
2389        let err = parse_err(r#"{"a": "foo"}"#);
2390        assert_eq!(
2391            err,
2392            "Json error: whilst decoding field 'a': expected { got \"foo\""
2393        );
2394
2395        let err = parse_err(r#"{"a": {"child": false}}"#);
2396        assert_eq!(
2397            err,
2398            "Json error: whilst decoding field 'a': whilst decoding field 'child': expected primitive got false"
2399        );
2400
2401        let err = parse_err(r#"{"a": {"child": []}}"#);
2402        assert_eq!(
2403            err,
2404            "Json error: whilst decoding field 'a': whilst decoding field 'child': expected primitive got []"
2405        );
2406
2407        let err = parse_err(r#"{"a": {"child": [123]}}"#);
2408        assert_eq!(
2409            err,
2410            "Json error: whilst decoding field 'a': whilst decoding field 'child': expected primitive got [123]"
2411        );
2412
2413        let err = parse_err(r#"{"a": {"child": [123, 3465346]}}"#);
2414        assert_eq!(
2415            err,
2416            "Json error: whilst decoding field 'a': whilst decoding field 'child': expected primitive got [123, 3465346]"
2417        );
2418    }
2419
2420    #[test]
2421    fn test_serialize_timestamp() {
2422        let json = vec![
2423            json!({"timestamp": 1681319393}),
2424            json!({"timestamp": "1970-01-01T00:00:00+02:00"}),
2425        ];
2426        let schema = Schema::new(vec![Field::new(
2427            "timestamp",
2428            DataType::Timestamp(TimeUnit::Second, None),
2429            true,
2430        )]);
2431        let mut decoder = ReaderBuilder::new(Arc::new(schema))
2432            .build_decoder()
2433            .unwrap();
2434        decoder.serialize(&json).unwrap();
2435        let batch = decoder.flush().unwrap().unwrap();
2436        assert_eq!(batch.num_rows(), 2);
2437        assert_eq!(batch.num_columns(), 1);
2438        let values = batch.column(0).as_primitive::<TimestampSecondType>();
2439        assert_eq!(values.values(), &[1681319393, -7200]);
2440    }
2441
2442    #[test]
2443    fn test_serialize_decimal() {
2444        let json = vec![
2445            json!({"decimal": 1.234}),
2446            json!({"decimal": "1.234"}),
2447            json!({"decimal": 1234}),
2448            json!({"decimal": "1234"}),
2449        ];
2450        let schema = Schema::new(vec![Field::new(
2451            "decimal",
2452            DataType::Decimal128(10, 3),
2453            true,
2454        )]);
2455        let mut decoder = ReaderBuilder::new(Arc::new(schema))
2456            .build_decoder()
2457            .unwrap();
2458        decoder.serialize(&json).unwrap();
2459        let batch = decoder.flush().unwrap().unwrap();
2460        assert_eq!(batch.num_rows(), 4);
2461        assert_eq!(batch.num_columns(), 1);
2462        let values = batch.column(0).as_primitive::<Decimal128Type>();
2463        assert_eq!(values.values(), &[1234, 1234, 1234000, 1234000]);
2464    }
2465
2466    #[test]
2467    fn test_serde_field() {
2468        let field = Field::new("int", DataType::Int32, true);
2469        let mut decoder = ReaderBuilder::new_with_field(field)
2470            .build_decoder()
2471            .unwrap();
2472        decoder.serialize(&[1_i32, 2, 3, 4]).unwrap();
2473        let b = decoder.flush().unwrap().unwrap();
2474        let values = b.column(0).as_primitive::<Int32Type>().values();
2475        assert_eq!(values, &[1, 2, 3, 4]);
2476    }
2477
2478    #[test]
2479    fn test_serde_large_numbers() {
2480        let field = Field::new("int", DataType::Int64, true);
2481        let mut decoder = ReaderBuilder::new_with_field(field)
2482            .build_decoder()
2483            .unwrap();
2484
2485        decoder.serialize(&[1699148028689_u64, 2, 3, 4]).unwrap();
2486        let b = decoder.flush().unwrap().unwrap();
2487        let values = b.column(0).as_primitive::<Int64Type>().values();
2488        assert_eq!(values, &[1699148028689, 2, 3, 4]);
2489
2490        let field = Field::new(
2491            "int",
2492            DataType::Timestamp(TimeUnit::Microsecond, None),
2493            true,
2494        );
2495        let mut decoder = ReaderBuilder::new_with_field(field)
2496            .build_decoder()
2497            .unwrap();
2498
2499        decoder.serialize(&[1699148028689_u64, 2, 3, 4]).unwrap();
2500        let b = decoder.flush().unwrap().unwrap();
2501        let values = b
2502            .column(0)
2503            .as_primitive::<TimestampMicrosecondType>()
2504            .values();
2505        assert_eq!(values, &[1699148028689, 2, 3, 4]);
2506    }
2507
2508    #[test]
2509    fn test_coercing_primitive_into_string_decoder() {
2510        let buf = &format!(
2511            r#"[{{"a": 1, "b": "A", "c": "T"}}, {{"a": 2, "b": "BB", "c": "F"}}, {{"a": {}, "b": 123, "c": false}}, {{"a": {}, "b": 789, "c": true}}]"#,
2512            (i32::MAX as i64 + 10),
2513            i64::MAX - 10
2514        );
2515        let schema = Schema::new(vec![
2516            Field::new("a", DataType::Float64, true),
2517            Field::new("b", DataType::Utf8, true),
2518            Field::new("c", DataType::Utf8, true),
2519        ]);
2520        let json_array: Vec<serde_json::Value> = serde_json::from_str(buf).unwrap();
2521        let schema_ref = Arc::new(schema);
2522
2523        // read record batches
2524        let reader = ReaderBuilder::new(schema_ref.clone()).with_coerce_primitive(true);
2525        let mut decoder = reader.build_decoder().unwrap();
2526        decoder.serialize(json_array.as_slice()).unwrap();
2527        let batch = decoder.flush().unwrap().unwrap();
2528        assert_eq!(
2529            batch,
2530            RecordBatch::try_new(
2531                schema_ref,
2532                vec![
2533                    Arc::new(Float64Array::from(vec![
2534                        1.0,
2535                        2.0,
2536                        (i32::MAX as i64 + 10) as f64,
2537                        (i64::MAX - 10) as f64
2538                    ])),
2539                    Arc::new(StringArray::from(vec!["A", "BB", "123", "789"])),
2540                    Arc::new(StringArray::from(vec!["T", "F", "false", "true"])),
2541                ]
2542            )
2543            .unwrap()
2544        );
2545    }
2546
2547    // Parse the given `row` in `struct_mode` as a type given by fields.
2548    //
2549    // If as_struct == true, wrap the fields in a Struct field with name "r".
2550    // If as_struct == false, wrap the fields in a Schema.
2551    fn _parse_structs(
2552        row: &str,
2553        struct_mode: StructMode,
2554        fields: Fields,
2555        as_struct: bool,
2556    ) -> Result<RecordBatch, ArrowError> {
2557        let builder = if as_struct {
2558            ReaderBuilder::new_with_field(Field::new("r", DataType::Struct(fields), true))
2559        } else {
2560            ReaderBuilder::new(Arc::new(Schema::new(fields)))
2561        };
2562        builder
2563            .with_struct_mode(struct_mode)
2564            .build(Cursor::new(row.as_bytes()))
2565            .unwrap()
2566            .next()
2567            .unwrap()
2568    }
2569
2570    #[test]
2571    fn test_struct_decoding_list_length() {
2572        use arrow_array::array;
2573
2574        let row = "[1, 2]";
2575
2576        let mut fields = vec![Field::new("a", DataType::Int32, true)];
2577        let too_few_fields = Fields::from(fields.clone());
2578        fields.push(Field::new("b", DataType::Int32, true));
2579        let correct_fields = Fields::from(fields.clone());
2580        fields.push(Field::new("c", DataType::Int32, true));
2581        let too_many_fields = Fields::from(fields.clone());
2582
2583        let parse = |fields: Fields, as_struct: bool| {
2584            _parse_structs(row, StructMode::ListOnly, fields, as_struct)
2585        };
2586
2587        let expected_row = StructArray::new(
2588            correct_fields.clone(),
2589            vec![
2590                Arc::new(array::Int32Array::from(vec![1])),
2591                Arc::new(array::Int32Array::from(vec![2])),
2592            ],
2593            None,
2594        );
2595        let row_field = Field::new("r", DataType::Struct(correct_fields.clone()), true);
2596
2597        assert_eq!(
2598            parse(too_few_fields.clone(), true).unwrap_err().to_string(),
2599            "Json error: found extra columns for 1 fields".to_string()
2600        );
2601        assert_eq!(
2602            parse(too_few_fields, false).unwrap_err().to_string(),
2603            "Json error: found extra columns for 1 fields".to_string()
2604        );
2605        assert_eq!(
2606            parse(correct_fields.clone(), true).unwrap(),
2607            RecordBatch::try_new(
2608                Arc::new(Schema::new(vec![row_field])),
2609                vec![Arc::new(expected_row.clone())]
2610            )
2611            .unwrap()
2612        );
2613        assert_eq!(
2614            parse(correct_fields, false).unwrap(),
2615            RecordBatch::from(expected_row)
2616        );
2617        assert_eq!(
2618            parse(too_many_fields.clone(), true)
2619                .unwrap_err()
2620                .to_string(),
2621            "Json error: found 2 columns for 3 fields".to_string()
2622        );
2623        assert_eq!(
2624            parse(too_many_fields, false).unwrap_err().to_string(),
2625            "Json error: found 2 columns for 3 fields".to_string()
2626        );
2627    }
2628
2629    #[test]
2630    fn test_struct_decoding() {
2631        use arrow_array::builder;
2632
2633        let nested_object_json = r#"{"a": {"b": [1, 2], "c": {"d": 3}}}"#;
2634        let nested_list_json = r#"[[[1, 2], {"d": 3}]]"#;
2635        let nested_mixed_json = r#"{"a": [[1, 2], {"d": 3}]}"#;
2636
2637        let struct_fields = Fields::from(vec![
2638            Field::new("b", DataType::new_list(DataType::Int32, true), true),
2639            Field::new_map(
2640                "c",
2641                "entries",
2642                Field::new("keys", DataType::Utf8, false),
2643                Field::new("values", DataType::Int32, true),
2644                false,
2645                false,
2646            ),
2647        ]);
2648
2649        let list_array =
2650            ListArray::from_iter_primitive::<Int32Type, _, _>(vec![Some(vec![Some(1), Some(2)])]);
2651
2652        let map_array = {
2653            let mut map_builder = builder::MapBuilder::new(
2654                None,
2655                builder::StringBuilder::new(),
2656                builder::Int32Builder::new(),
2657            );
2658            map_builder.keys().append_value("d");
2659            map_builder.values().append_value(3);
2660            map_builder.append(true).unwrap();
2661            map_builder.finish()
2662        };
2663
2664        let struct_array = StructArray::new(
2665            struct_fields.clone(),
2666            vec![Arc::new(list_array), Arc::new(map_array)],
2667            None,
2668        );
2669
2670        let fields = Fields::from(vec![Field::new("a", DataType::Struct(struct_fields), true)]);
2671        let schema = Arc::new(Schema::new(fields.clone()));
2672        let expected = RecordBatch::try_new(schema.clone(), vec![Arc::new(struct_array)]).unwrap();
2673
2674        let parse = |row: &str, struct_mode: StructMode| {
2675            _parse_structs(row, struct_mode, fields.clone(), false)
2676        };
2677
2678        assert_eq!(
2679            parse(nested_object_json, StructMode::ObjectOnly).unwrap(),
2680            expected
2681        );
2682        assert_eq!(
2683            parse(nested_list_json, StructMode::ObjectOnly)
2684                .unwrap_err()
2685                .to_string(),
2686            "Json error: expected { got [[[1, 2], {\"d\": 3}]]".to_owned()
2687        );
2688        assert_eq!(
2689            parse(nested_mixed_json, StructMode::ObjectOnly)
2690                .unwrap_err()
2691                .to_string(),
2692            "Json error: whilst decoding field 'a': expected { got [[1, 2], {\"d\": 3}]".to_owned()
2693        );
2694
2695        assert_eq!(
2696            parse(nested_list_json, StructMode::ListOnly).unwrap(),
2697            expected
2698        );
2699        assert_eq!(
2700            parse(nested_object_json, StructMode::ListOnly)
2701                .unwrap_err()
2702                .to_string(),
2703            "Json error: expected [ got {\"a\": {\"b\": [1, 2]\"c\": {\"d\": 3}}}".to_owned()
2704        );
2705        assert_eq!(
2706            parse(nested_mixed_json, StructMode::ListOnly)
2707                .unwrap_err()
2708                .to_string(),
2709            "Json error: expected [ got {\"a\": [[1, 2], {\"d\": 3}]}".to_owned()
2710        );
2711    }
2712
2713    // Test cases:
2714    // [] -> RecordBatch row with no entries.  Schema = [('a', Int32)] -> Error
2715    // [] -> RecordBatch row with no entries. Schema = [('r', [('a', Int32)])] -> Error
2716    // [] -> StructArray row with no entries. Fields [('a', Int32')] -> Error
2717    // [[]] -> RecordBatch row with empty struct entry. Schema = [('r', [('a', Int32)])] -> Error
2718    #[test]
2719    fn test_struct_decoding_empty_list() {
2720        let int_field = Field::new("a", DataType::Int32, true);
2721        let struct_field = Field::new(
2722            "r",
2723            DataType::Struct(Fields::from(vec![int_field.clone()])),
2724            true,
2725        );
2726
2727        let parse = |row: &str, as_struct: bool, field: Field| {
2728            _parse_structs(
2729                row,
2730                StructMode::ListOnly,
2731                Fields::from(vec![field]),
2732                as_struct,
2733            )
2734        };
2735
2736        // Missing fields
2737        assert_eq!(
2738            parse("[]", true, struct_field.clone())
2739                .unwrap_err()
2740                .to_string(),
2741            "Json error: found 0 columns for 1 fields".to_owned()
2742        );
2743        assert_eq!(
2744            parse("[]", false, int_field.clone())
2745                .unwrap_err()
2746                .to_string(),
2747            "Json error: found 0 columns for 1 fields".to_owned()
2748        );
2749        assert_eq!(
2750            parse("[]", false, struct_field.clone())
2751                .unwrap_err()
2752                .to_string(),
2753            "Json error: found 0 columns for 1 fields".to_owned()
2754        );
2755        assert_eq!(
2756            parse("[[]]", false, struct_field.clone())
2757                .unwrap_err()
2758                .to_string(),
2759            "Json error: whilst decoding field 'r': found 0 columns for 1 fields".to_owned()
2760        );
2761    }
2762
2763    #[test]
2764    fn test_decode_list_struct_with_wrong_types() {
2765        let int_field = Field::new("a", DataType::Int32, true);
2766        let struct_field = Field::new(
2767            "r",
2768            DataType::Struct(Fields::from(vec![int_field.clone()])),
2769            true,
2770        );
2771
2772        let parse = |row: &str, as_struct: bool, field: Field| {
2773            _parse_structs(
2774                row,
2775                StructMode::ListOnly,
2776                Fields::from(vec![field]),
2777                as_struct,
2778            )
2779        };
2780
2781        // Wrong values
2782        assert_eq!(
2783            parse(r#"[["a"]]"#, false, struct_field.clone())
2784                .unwrap_err()
2785                .to_string(),
2786            "Json error: whilst decoding field 'r': whilst decoding field 'a': failed to parse \"a\" as Int32".to_owned()
2787        );
2788        assert_eq!(
2789            parse(r#"[["a"]]"#, true, struct_field.clone())
2790                .unwrap_err()
2791                .to_string(),
2792            "Json error: whilst decoding field 'r': whilst decoding field 'a': failed to parse \"a\" as Int32".to_owned()
2793        );
2794        assert_eq!(
2795            parse(r#"["a"]"#, true, int_field.clone())
2796                .unwrap_err()
2797                .to_string(),
2798            "Json error: whilst decoding field 'a': failed to parse \"a\" as Int32".to_owned()
2799        );
2800        assert_eq!(
2801            parse(r#"["a"]"#, false, int_field.clone())
2802                .unwrap_err()
2803                .to_string(),
2804            "Json error: whilst decoding field 'a': failed to parse \"a\" as Int32".to_owned()
2805        );
2806    }
2807}