use std::io::{BufRead, BufReader, Read, Seek, SeekFrom};
use std::iter::FromIterator;
use std::sync::Arc;
use indexmap::map::IndexMap as HashMap;
use indexmap::set::IndexSet as HashSet;
use serde_json::Value;
use crate::buffer::MutableBuffer;
use crate::datatypes::*;
use crate::error::{ArrowError, Result};
use crate::record_batch::RecordBatch;
use crate::util::bit_util;
use crate::{array::*, buffer::Buffer};
fn coerce_data_type(dt: Vec<&DataType>) -> Result<DataType> {
match dt.len() {
1 => Ok(dt[0].clone()),
2 => {
if dt.contains(&&DataType::List(Box::new(Field::new(
"item",
DataType::Float64,
true,
)))) || dt.contains(&&DataType::List(Box::new(Field::new(
"item",
DataType::Int64,
true,
)))) || dt.contains(&&DataType::List(Box::new(Field::new(
"item",
DataType::Boolean,
true,
)))) || dt.contains(&&DataType::List(Box::new(Field::new(
"item",
DataType::Utf8,
true,
)))) {
let mut dt = dt;
dt.sort();
match (dt[0], dt[1]) {
(t1, DataType::List(e)) if e.data_type() == &DataType::Float64 => {
if t1 == &DataType::Float64 {
Ok(DataType::List(Box::new(Field::new(
"item",
DataType::Float64,
true,
))))
} else {
Ok(DataType::List(Box::new(Field::new(
"item",
coerce_data_type(vec![t1, &DataType::Float64])?,
true,
))))
}
}
(t1, DataType::List(e)) if e.data_type() == &DataType::Int64 => {
if t1 == &DataType::Int64 {
Ok(DataType::List(Box::new(Field::new(
"item",
DataType::Int64,
true,
))))
} else {
Ok(DataType::List(Box::new(Field::new(
"item",
coerce_data_type(vec![t1, &DataType::Int64])?,
true,
))))
}
}
(t1, DataType::List(e)) if e.data_type() == &DataType::Boolean => {
if t1 == &DataType::Boolean {
Ok(DataType::List(Box::new(Field::new(
"item",
DataType::Boolean,
true,
))))
} else {
Ok(DataType::List(Box::new(Field::new(
"item",
coerce_data_type(vec![t1, &DataType::Boolean])?,
true,
))))
}
}
(t1, DataType::List(e)) if e.data_type() == &DataType::Utf8 => {
if t1 == &DataType::Utf8 {
Ok(DataType::List(Box::new(Field::new(
"item",
DataType::Utf8,
true,
))))
} else {
Ok(DataType::List(Box::new(Field::new(
"item",
coerce_data_type(vec![t1, &DataType::Utf8])?,
true,
))))
}
}
(t1, t2) => Err(ArrowError::JsonError(format!(
"Cannot coerce data types for {:?} and {:?}",
t1, t2
))),
}
} else if dt.contains(&&DataType::Float64) && dt.contains(&&DataType::Int64) {
Ok(DataType::Float64)
} else {
Ok(DataType::Utf8)
}
}
_ => {
Ok(DataType::List(Box::new(Field::new(
"item",
DataType::Utf8,
true,
))))
}
}
}
fn generate_schema(spec: HashMap<String, HashSet<DataType>>) -> Result<SchemaRef> {
let fields: Result<Vec<Field>> = spec
.iter()
.map(|(k, hs)| {
let v: Vec<&DataType> = hs.iter().collect();
coerce_data_type(v).map(|t| Field::new(k, t, true))
})
.collect();
match fields {
Ok(fields) => {
let schema = Schema::new(fields);
Ok(Arc::new(schema))
}
Err(e) => Err(e),
}
}
#[derive(Debug)]
pub struct ValueIter<'a, R: Read> {
reader: &'a mut BufReader<R>,
max_read_records: Option<usize>,
record_count: usize,
line_buf: String,
}
impl<'a, R: Read> ValueIter<'a, R> {
pub fn new(reader: &'a mut BufReader<R>, max_read_records: Option<usize>) -> Self {
Self {
reader,
max_read_records,
record_count: 0,
line_buf: String::new(),
}
}
}
impl<'a, R: Read> Iterator for ValueIter<'a, R> {
type Item = Result<Value>;
fn next(&mut self) -> Option<Self::Item> {
if let Some(max) = self.max_read_records {
if self.record_count >= max {
return None;
}
}
loop {
self.line_buf.truncate(0);
match self.reader.read_line(&mut self.line_buf) {
Ok(0) => {
return None;
}
Err(e) => {
return Some(Err(ArrowError::JsonError(format!(
"Failed to read JSON record: {}",
e
))));
}
_ => {
let trimmed_s = self.line_buf.trim();
if trimmed_s.is_empty() {
continue;
}
self.record_count += 1;
return Some(serde_json::from_str(trimmed_s).map_err(|e| {
ArrowError::JsonError(format!("Not valid JSON: {}", e))
}));
}
}
}
}
}
pub fn infer_json_schema_from_seekable<R: Read + Seek>(
reader: &mut BufReader<R>,
max_read_records: Option<usize>,
) -> Result<SchemaRef> {
let schema = infer_json_schema(reader, max_read_records);
reader.seek(SeekFrom::Start(0))?;
schema
}
pub fn infer_json_schema<R: Read>(
reader: &mut BufReader<R>,
max_read_records: Option<usize>,
) -> Result<SchemaRef> {
infer_json_schema_from_iterator(ValueIter::new(reader, max_read_records))
}
pub fn infer_json_schema_from_iterator<I>(value_iter: I) -> Result<SchemaRef>
where
I: Iterator<Item = Result<Value>>,
{
let mut values: HashMap<String, HashSet<DataType>> = HashMap::new();
for record in value_iter {
match record? {
Value::Object(map) => {
let res = map.iter().try_for_each(|(k, v)| {
match v {
Value::Array(a) => {
let types: Result<Vec<Option<&DataType>>> = a
.iter()
.map(|a| match a {
Value::Null => Ok(None),
Value::Number(n) => {
if n.is_i64() {
Ok(Some(&DataType::Int64))
} else {
Ok(Some(&DataType::Float64))
}
}
Value::Bool(_) => Ok(Some(&DataType::Boolean)),
Value::String(_) => Ok(Some(&DataType::Utf8)),
Value::Array(_) | Value::Object(_) => {
Err(ArrowError::JsonError(
"Nested lists and structs not supported"
.to_string(),
))
}
})
.collect();
match types {
Ok(types) => {
let mut types: Vec<&DataType> =
types.into_iter().filter_map(|t| t).collect();
types.dedup();
if !types.is_empty() {
let dt = coerce_data_type(types)?;
if values.contains_key(k) {
let x = values.get_mut(k).unwrap();
x.insert(DataType::List(Box::new(
Field::new("item", dt, true),
)));
} else {
let mut hs = HashSet::new();
hs.insert(DataType::List(Box::new(
Field::new("item", dt, true),
)));
values.insert(k.to_string(), hs);
}
}
Ok(())
}
Err(e) => Err(e),
}
}
Value::Bool(_) => {
if values.contains_key(k) {
let x = values.get_mut(k).unwrap();
x.insert(DataType::Boolean);
} else {
let mut hs = HashSet::new();
hs.insert(DataType::Boolean);
values.insert(k.to_string(), hs);
}
Ok(())
}
Value::Null => {
Ok(())
}
Value::Number(n) => {
if n.is_f64() {
if values.contains_key(k) {
let x = values.get_mut(k).unwrap();
x.insert(DataType::Float64);
} else {
let mut hs = HashSet::new();
hs.insert(DataType::Float64);
values.insert(k.to_string(), hs);
}
} else {
if values.contains_key(k) {
let x = values.get_mut(k).unwrap();
x.insert(DataType::Int64);
} else {
let mut hs = HashSet::new();
hs.insert(DataType::Int64);
values.insert(k.to_string(), hs);
}
}
Ok(())
}
Value::String(_) => {
if values.contains_key(k) {
let x = values.get_mut(k).unwrap();
x.insert(DataType::Utf8);
} else {
let mut hs = HashSet::new();
hs.insert(DataType::Utf8);
values.insert(k.to_string(), hs);
}
Ok(())
}
Value::Object(_) => Err(ArrowError::JsonError(
"Inferring schema from nested JSON structs currently not supported"
.to_string(),
)),
}
});
match res {
Ok(()) => {}
Err(e) => return Err(e),
}
}
value => {
return Err(ArrowError::JsonError(format!(
"Expected JSON record to be an object, found {:?}",
value
)));
}
};
}
generate_schema(values)
}
#[derive(Debug)]
pub struct Decoder {
schema: SchemaRef,
projection: Option<Vec<String>>,
batch_size: usize,
}
impl Decoder {
pub fn new(
schema: SchemaRef,
batch_size: usize,
projection: Option<Vec<String>>,
) -> Self {
Self {
schema,
projection,
batch_size,
}
}
pub fn schema(&self) -> SchemaRef {
match &self.projection {
Some(projection) => {
let fields = self.schema.fields();
let projected_fields: Vec<Field> = fields
.iter()
.filter_map(|field| {
if projection.contains(field.name()) {
Some(field.clone())
} else {
None
}
})
.collect();
Arc::new(Schema::new(projected_fields))
}
None => self.schema.clone(),
}
}
pub fn next_batch<I>(&self, value_iter: &mut I) -> Result<Option<RecordBatch>>
where
I: Iterator<Item = Result<Value>>,
{
let mut rows: Vec<Value> = Vec::with_capacity(self.batch_size);
for value in value_iter.by_ref().take(self.batch_size) {
let v = value?;
match v {
Value::Object(_) => rows.push(v),
_ => {
return Err(ArrowError::JsonError(format!(
"Row needs to be of type object, got: {:?}",
v
)));
}
}
}
if rows.is_empty() {
return Ok(None);
}
let rows = &rows[..];
let projection = self.projection.clone().unwrap_or_else(Vec::new);
let arrays = self.build_struct_array(rows, self.schema.fields(), &projection);
let projected_fields: Vec<Field> = if projection.is_empty() {
self.schema.fields().to_vec()
} else {
projection
.iter()
.map(|name| self.schema.column_with_name(name))
.filter_map(|c| c)
.map(|(_, field)| field.clone())
.collect()
};
let projected_schema = Arc::new(Schema::new(projected_fields));
arrays.and_then(|arr| RecordBatch::try_new(projected_schema, arr).map(Some))
}
fn build_wrapped_list_array(
&self,
rows: &[Value],
col_name: &str,
key_type: &DataType,
) -> Result<ArrayRef> {
match *key_type {
DataType::Int8 => {
let dtype = DataType::Dictionary(
Box::new(DataType::Int8),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<Int8Type>(&dtype, col_name, rows)
}
DataType::Int16 => {
let dtype = DataType::Dictionary(
Box::new(DataType::Int16),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<Int16Type>(&dtype, col_name, rows)
}
DataType::Int32 => {
let dtype = DataType::Dictionary(
Box::new(DataType::Int32),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<Int32Type>(&dtype, col_name, rows)
}
DataType::Int64 => {
let dtype = DataType::Dictionary(
Box::new(DataType::Int64),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<Int64Type>(&dtype, col_name, rows)
}
DataType::UInt8 => {
let dtype = DataType::Dictionary(
Box::new(DataType::UInt8),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<UInt8Type>(&dtype, col_name, rows)
}
DataType::UInt16 => {
let dtype = DataType::Dictionary(
Box::new(DataType::UInt16),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<UInt16Type>(&dtype, col_name, rows)
}
DataType::UInt32 => {
let dtype = DataType::Dictionary(
Box::new(DataType::UInt32),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<UInt32Type>(&dtype, col_name, rows)
}
DataType::UInt64 => {
let dtype = DataType::Dictionary(
Box::new(DataType::UInt64),
Box::new(DataType::Utf8),
);
self.list_array_string_array_builder::<UInt64Type>(&dtype, col_name, rows)
}
ref e => Err(ArrowError::JsonError(format!(
"Data type is currently not supported for dictionaries in list : {:?}",
e
))),
}
}
#[inline(always)]
fn list_array_string_array_builder<DICT_TY>(
&self,
data_type: &DataType,
col_name: &str,
rows: &[Value],
) -> Result<ArrayRef>
where
DICT_TY: ArrowPrimitiveType + ArrowDictionaryKeyType,
{
let mut builder: Box<dyn ArrayBuilder> = match data_type {
DataType::Utf8 => {
let values_builder = StringBuilder::new(rows.len() * 5);
Box::new(ListBuilder::new(values_builder))
}
DataType::Dictionary(_, _) => {
let values_builder =
self.build_string_dictionary_builder::<DICT_TY>(rows.len() * 5)?;
Box::new(ListBuilder::new(values_builder))
}
e => {
return Err(ArrowError::JsonError(format!(
"Nested list data builder type is not supported: {:?}",
e
)))
}
};
for row in rows {
if let Some(value) = row.get(col_name) {
let vals: Vec<Option<String>> = if let Value::String(v) = value {
vec![Some(v.to_string())]
} else if let Value::Array(n) = value {
n.iter()
.map(|v: &Value| {
if v.is_string() {
Some(v.as_str().unwrap().to_string())
} else if v.is_array() || v.is_object() || v.is_null() {
None
} else {
Some(v.to_string())
}
})
.collect()
} else if let Value::Null = value {
vec![None]
} else if !value.is_object() {
vec![Some(value.to_string())]
} else {
return Err(ArrowError::JsonError(
"Only scalars are currently supported in JSON arrays".to_string(),
));
};
match data_type {
DataType::Utf8 => {
let builder = builder
.as_any_mut()
.downcast_mut::<ListBuilder<StringBuilder>>()
.ok_or_else(||ArrowError::JsonError(
"Cast failed for ListBuilder<StringBuilder> during nested data parsing".to_string(),
))?;
for val in vals {
if let Some(v) = val {
builder.values().append_value(&v)?
} else {
builder.values().append_null()?
};
}
builder.append(true)?;
}
DataType::Dictionary(_, _) => {
let builder = builder.as_any_mut().downcast_mut::<ListBuilder<StringDictionaryBuilder<DICT_TY>>>().ok_or_else(||ArrowError::JsonError(
"Cast failed for ListBuilder<StringDictionaryBuilder> during nested data parsing".to_string(),
))?;
for val in vals {
if let Some(v) = val {
let _ = builder.values().append(&v)?;
} else {
builder.values().append_null()?
};
}
builder.append(true)?;
}
e => {
return Err(ArrowError::JsonError(format!(
"Nested list data builder type is not supported: {:?}",
e
)))
}
}
}
}
Ok(builder.finish() as ArrayRef)
}
#[inline(always)]
fn build_string_dictionary_builder<T>(
&self,
row_len: usize,
) -> Result<StringDictionaryBuilder<T>>
where
T: ArrowPrimitiveType + ArrowDictionaryKeyType,
{
let key_builder = PrimitiveBuilder::<T>::new(row_len);
let values_builder = StringBuilder::new(row_len * 5);
Ok(StringDictionaryBuilder::new(key_builder, values_builder))
}
#[inline(always)]
fn build_string_dictionary_array(
&self,
rows: &[Value],
col_name: &str,
key_type: &DataType,
value_type: &DataType,
) -> Result<ArrayRef> {
if let DataType::Utf8 = *value_type {
match *key_type {
DataType::Int8 => self.build_dictionary_array::<Int8Type>(rows, col_name),
DataType::Int16 => {
self.build_dictionary_array::<Int16Type>(rows, col_name)
}
DataType::Int32 => {
self.build_dictionary_array::<Int32Type>(rows, col_name)
}
DataType::Int64 => {
self.build_dictionary_array::<Int64Type>(rows, col_name)
}
DataType::UInt8 => {
self.build_dictionary_array::<UInt8Type>(rows, col_name)
}
DataType::UInt16 => {
self.build_dictionary_array::<UInt16Type>(rows, col_name)
}
DataType::UInt32 => {
self.build_dictionary_array::<UInt32Type>(rows, col_name)
}
DataType::UInt64 => {
self.build_dictionary_array::<UInt64Type>(rows, col_name)
}
_ => Err(ArrowError::JsonError(
"unsupported dictionary key type".to_string(),
)),
}
} else {
Err(ArrowError::JsonError(
"dictionary types other than UTF-8 not yet supported".to_string(),
))
}
}
fn build_boolean_array(&self, rows: &[Value], col_name: &str) -> Result<ArrayRef> {
let mut builder = BooleanBuilder::new(rows.len());
for row in rows {
if let Some(value) = row.get(&col_name) {
if let Some(boolean) = value.as_bool() {
builder.append_value(boolean)?
} else {
builder.append_null()?;
}
} else {
builder.append_null()?;
}
}
Ok(Arc::new(builder.finish()))
}
fn build_primitive_array<T: ArrowPrimitiveType>(
&self,
rows: &[Value],
col_name: &str,
) -> Result<ArrayRef>
where
T: ArrowNumericType,
T::Native: num::NumCast,
{
Ok(Arc::new(
rows.iter()
.map(|row| {
row.get(&col_name)
.and_then(|value| value.as_f64())
.and_then(num::cast::cast)
})
.collect::<PrimitiveArray<T>>(),
))
}
fn build_nested_list_array<OffsetSize: OffsetSizeTrait>(
&self,
rows: &[Value],
list_field: &Field,
) -> Result<ArrayRef> {
let mut cur_offset = OffsetSize::zero();
let list_len = rows.len();
let num_list_bytes = bit_util::ceil(list_len, 8);
let mut offsets = Vec::with_capacity(list_len + 1);
let mut list_nulls =
MutableBuffer::new(num_list_bytes).with_bitset(num_list_bytes, false);
offsets.push(cur_offset);
rows.iter().enumerate().for_each(|(i, v)| {
if let Value::Array(a) = v {
cur_offset += OffsetSize::from_usize(a.len()).unwrap();
bit_util::set_bit(list_nulls.as_slice_mut(), i);
} else if let Value::Null = v {
} else {
cur_offset += OffsetSize::one();
}
offsets.push(cur_offset);
});
let valid_len = cur_offset.to_usize().unwrap();
let array_data = match list_field.data_type() {
DataType::Null => NullArray::new(valid_len).data(),
DataType::Boolean => {
let num_bytes = bit_util::ceil(valid_len, 8);
let mut bool_values =
MutableBuffer::new(num_bytes).with_bitset(num_bytes, false);
let mut bool_nulls =
MutableBuffer::new(num_bytes).with_bitset(num_bytes, true);
let mut curr_index = 0;
rows.iter().for_each(|v| {
if let Value::Array(vs) = v {
vs.iter().for_each(|value| {
if let Value::Bool(child) = value {
if *child {
bit_util::set_bit(
bool_values.as_slice_mut(),
curr_index,
);
}
} else {
bit_util::unset_bit(
bool_nulls.as_slice_mut(),
curr_index,
);
}
curr_index += 1;
});
}
});
ArrayData::builder(list_field.data_type().clone())
.len(valid_len)
.add_buffer(bool_values.into())
.null_bit_buffer(bool_nulls.into())
.build()
}
DataType::Int8 => self.read_primitive_list_values::<Int8Type>(rows),
DataType::Int16 => self.read_primitive_list_values::<Int16Type>(rows),
DataType::Int32 => self.read_primitive_list_values::<Int32Type>(rows),
DataType::Int64 => self.read_primitive_list_values::<Int64Type>(rows),
DataType::UInt8 => self.read_primitive_list_values::<UInt8Type>(rows),
DataType::UInt16 => self.read_primitive_list_values::<UInt16Type>(rows),
DataType::UInt32 => self.read_primitive_list_values::<UInt32Type>(rows),
DataType::UInt64 => self.read_primitive_list_values::<UInt64Type>(rows),
DataType::Float16 => {
return Err(ArrowError::JsonError("Float16 not supported".to_string()))
}
DataType::Float32 => self.read_primitive_list_values::<Float32Type>(rows),
DataType::Float64 => self.read_primitive_list_values::<Float64Type>(rows),
DataType::Timestamp(_, _)
| DataType::Date32(_)
| DataType::Date64(_)
| DataType::Time32(_)
| DataType::Time64(_) => {
return Err(ArrowError::JsonError(
"Temporal types are not yet supported, see ARROW-4803".to_string(),
))
}
DataType::Utf8 => {
StringArray::from_iter(flatten_json_string_values(rows).into_iter())
.data()
}
DataType::LargeUtf8 => {
LargeStringArray::from_iter(flatten_json_string_values(rows).into_iter())
.data()
}
DataType::List(field) => {
let child = self
.build_nested_list_array::<i32>(&flatten_json_values(rows), field)?;
child.data()
}
DataType::LargeList(field) => {
let child = self
.build_nested_list_array::<i64>(&flatten_json_values(rows), field)?;
child.data()
}
DataType::Struct(fields) => {
let len = rows.len();
let num_bytes = bit_util::ceil(len, 8);
let mut null_buffer =
MutableBuffer::new(num_bytes).with_bitset(num_bytes, false);
let mut struct_index = 0;
let rows: Vec<Value> = rows
.iter()
.flat_map(|row| {
if let Value::Array(values) = row {
values.iter().for_each(|_| {
bit_util::set_bit(
null_buffer.as_slice_mut(),
struct_index,
);
struct_index += 1;
});
values.clone()
} else {
struct_index += 1;
vec![Value::Null]
}
})
.collect();
let arrays =
self.build_struct_array(rows.as_slice(), fields.as_slice(), &[])?;
let data_type = DataType::Struct(fields.clone());
let buf = null_buffer.into();
ArrayDataBuilder::new(data_type)
.len(rows.len())
.null_bit_buffer(buf)
.child_data(arrays.into_iter().map(|a| a.data()).collect())
.build()
}
datatype => {
return Err(ArrowError::JsonError(format!(
"Nested list of {:?} not supported",
datatype
)));
}
};
let list_data = ArrayData::builder(DataType::List(Box::new(list_field.clone())))
.len(list_len)
.add_buffer(Buffer::from(offsets.to_byte_slice()))
.add_child_data(array_data)
.null_bit_buffer(list_nulls.into())
.build();
Ok(Arc::new(GenericListArray::<OffsetSize>::from(list_data)))
}
fn build_struct_array(
&self,
rows: &[Value],
struct_fields: &[Field],
projection: &[String],
) -> Result<Vec<ArrayRef>> {
let arrays: Result<Vec<ArrayRef>> = struct_fields
.iter()
.filter(|field| projection.is_empty() || projection.contains(field.name()))
.map(|field| {
match field.data_type() {
DataType::Null => {
Ok(Arc::new(NullArray::new(rows.len())) as ArrayRef)
}
DataType::Boolean => self.build_boolean_array(rows, field.name()),
DataType::Float64 => {
self.build_primitive_array::<Float64Type>(rows, field.name())
}
DataType::Float32 => {
self.build_primitive_array::<Float32Type>(rows, field.name())
}
DataType::Int64 => {
self.build_primitive_array::<Int64Type>(rows, field.name())
}
DataType::Int32 => {
self.build_primitive_array::<Int32Type>(rows, field.name())
}
DataType::Int16 => {
self.build_primitive_array::<Int16Type>(rows, field.name())
}
DataType::Int8 => {
self.build_primitive_array::<Int8Type>(rows, field.name())
}
DataType::UInt64 => {
self.build_primitive_array::<UInt64Type>(rows, field.name())
}
DataType::UInt32 => {
self.build_primitive_array::<UInt32Type>(rows, field.name())
}
DataType::UInt16 => {
self.build_primitive_array::<UInt16Type>(rows, field.name())
}
DataType::UInt8 => {
self.build_primitive_array::<UInt8Type>(rows, field.name())
}
DataType::Timestamp(unit, _) => match unit {
TimeUnit::Second => self
.build_primitive_array::<TimestampSecondType>(
rows,
field.name(),
),
TimeUnit::Microsecond => self
.build_primitive_array::<TimestampMicrosecondType>(
rows,
field.name(),
),
TimeUnit::Millisecond => self
.build_primitive_array::<TimestampMillisecondType>(
rows,
field.name(),
),
TimeUnit::Nanosecond => self
.build_primitive_array::<TimestampNanosecondType>(
rows,
field.name(),
),
},
DataType::Date64(_) => {
self.build_primitive_array::<Date64Type>(rows, field.name())
}
DataType::Date32(_) => {
self.build_primitive_array::<Date32Type>(rows, field.name())
}
DataType::Time64(unit) => match unit {
TimeUnit::Microsecond => self
.build_primitive_array::<Time64MicrosecondType>(
rows,
field.name(),
),
TimeUnit::Nanosecond => self
.build_primitive_array::<Time64NanosecondType>(
rows,
field.name(),
),
t => Err(ArrowError::JsonError(format!(
"TimeUnit {:?} not supported with Time64",
t
))),
},
DataType::Time32(unit) => match unit {
TimeUnit::Second => self
.build_primitive_array::<Time32SecondType>(
rows,
field.name(),
),
TimeUnit::Millisecond => self
.build_primitive_array::<Time32MillisecondType>(
rows,
field.name(),
),
t => Err(ArrowError::JsonError(format!(
"TimeUnit {:?} not supported with Time32",
t
))),
},
DataType::Utf8 => Ok(Arc::new(
rows.iter()
.map(|row| {
let maybe_value = row.get(field.name());
maybe_value.and_then(|value| value.as_str())
})
.collect::<StringArray>(),
) as ArrayRef),
DataType::List(ref list_field) => {
match list_field.data_type() {
DataType::Dictionary(ref key_ty, _) => {
self.build_wrapped_list_array(rows, field.name(), key_ty)
}
_ => {
let extracted_rows = rows
.iter()
.map(|row| {
row.get(field.name())
.cloned()
.unwrap_or(Value::Null)
})
.collect::<Vec<Value>>();
self.build_nested_list_array::<i32>(
extracted_rows.as_slice(),
list_field,
)
}
}
}
DataType::Dictionary(ref key_ty, ref val_ty) => self
.build_string_dictionary_array(
rows,
field.name(),
key_ty,
val_ty,
),
DataType::Struct(fields) => {
let len = rows.len();
let num_bytes = bit_util::ceil(len, 8);
let mut null_buffer =
MutableBuffer::new(num_bytes).with_bitset(num_bytes, false);
let struct_rows = rows
.iter()
.enumerate()
.map(|(i, row)| {
(
i,
row.as_object()
.map(|v| v.get(field.name()))
.flatten(),
)
})
.map(|(i, v)| match v {
Some(Value::Object(value)) => {
bit_util::set_bit(null_buffer.as_slice_mut(), i);
Value::Object(value.clone())
}
_ => Value::Object(Default::default()),
})
.collect::<Vec<Value>>();
let arrays =
self.build_struct_array(&struct_rows, fields, &[])?;
let data_type = DataType::Struct(fields.clone());
let data = ArrayDataBuilder::new(data_type)
.len(len)
.null_bit_buffer(null_buffer.into())
.child_data(arrays.into_iter().map(|a| a.data()).collect())
.build();
Ok(make_array(data))
}
_ => Err(ArrowError::JsonError(format!(
"{:?} type is not supported",
field.data_type()
))),
}
})
.collect();
arrays
}
#[inline(always)]
fn build_dictionary_array<T>(
&self,
rows: &[Value],
col_name: &str,
) -> Result<ArrayRef>
where
T::Native: num::NumCast,
T: ArrowPrimitiveType + ArrowDictionaryKeyType,
{
let mut builder: StringDictionaryBuilder<T> =
self.build_string_dictionary_builder(rows.len())?;
for row in rows {
if let Some(value) = row.get(&col_name) {
if let Some(str_v) = value.as_str() {
builder.append(str_v).map(drop)?
} else {
builder.append_null()?
}
} else {
builder.append_null()?
}
}
Ok(Arc::new(builder.finish()) as ArrayRef)
}
fn read_primitive_list_values<T>(&self, rows: &[Value]) -> ArrayDataRef
where
T: ArrowPrimitiveType + ArrowNumericType,
T::Native: num::NumCast,
{
let values = rows
.iter()
.flat_map(|row| {
if let Value::Array(values) = row {
values
.iter()
.map(|value| {
let v: Option<T::Native> =
value.as_f64().and_then(num::cast::cast);
v
})
.collect::<Vec<Option<T::Native>>>()
} else if let Value::Number(value) = row {
let v: Option<T::Native> = value.as_f64().and_then(num::cast::cast);
v.map(|v| vec![Some(v)]).unwrap_or_default()
} else {
vec![]
}
})
.collect::<Vec<Option<T::Native>>>();
let array = PrimitiveArray::<T>::from_iter(values.iter());
array.data()
}
}
#[inline(always)]
fn json_value_as_string(value: &Value) -> Option<String> {
match value {
Value::Null => None,
Value::String(string) => Some(string.clone()),
_ => Some(value.to_string()),
}
}
#[inline]
fn flatten_json_values(values: &[Value]) -> Vec<Value> {
values
.iter()
.flat_map(|row| {
if let Value::Array(values) = row {
values.clone()
} else if let Value::Null = row {
vec![Value::Null]
} else {
vec![row.clone()]
}
})
.collect()
}
#[inline]
fn flatten_json_string_values(values: &[Value]) -> Vec<Option<String>> {
values
.iter()
.flat_map(|row| {
if let Value::Array(values) = row {
values
.iter()
.map(json_value_as_string)
.collect::<Vec<Option<_>>>()
} else if let Value::Null = row {
vec![]
} else {
vec![json_value_as_string(row)]
}
})
.collect::<Vec<Option<_>>>()
}
#[derive(Debug)]
pub struct Reader<R: Read> {
reader: BufReader<R>,
decoder: Decoder,
}
impl<R: Read> Reader<R> {
pub fn new(
reader: R,
schema: SchemaRef,
batch_size: usize,
projection: Option<Vec<String>>,
) -> Self {
Self::from_buf_reader(BufReader::new(reader), schema, batch_size, projection)
}
pub fn from_buf_reader(
reader: BufReader<R>,
schema: SchemaRef,
batch_size: usize,
projection: Option<Vec<String>>,
) -> Self {
Self {
reader,
decoder: Decoder::new(schema, batch_size, projection),
}
}
pub fn schema(&self) -> SchemaRef {
self.decoder.schema()
}
#[allow(clippy::should_implement_trait)]
pub fn next(&mut self) -> Result<Option<RecordBatch>> {
self.decoder
.next_batch(&mut ValueIter::new(&mut self.reader, None))
}
}
#[derive(Debug)]
pub struct ReaderBuilder {
schema: Option<SchemaRef>,
max_records: Option<usize>,
batch_size: usize,
projection: Option<Vec<String>>,
}
impl Default for ReaderBuilder {
fn default() -> Self {
Self {
schema: None,
max_records: None,
batch_size: 1024,
projection: None,
}
}
}
impl ReaderBuilder {
pub fn new() -> Self {
Self::default()
}
pub fn with_schema(mut self, schema: SchemaRef) -> Self {
self.schema = Some(schema);
self
}
pub fn infer_schema(mut self, max_records: Option<usize>) -> Self {
self.schema = None;
self.max_records = max_records;
self
}
pub fn with_batch_size(mut self, batch_size: usize) -> Self {
self.batch_size = batch_size;
self
}
pub fn with_projection(mut self, projection: Vec<String>) -> Self {
self.projection = Some(projection);
self
}
pub fn build<R>(self, source: R) -> Result<Reader<R>>
where
R: Read + Seek,
{
let mut buf_reader = BufReader::new(source);
let schema = match self.schema {
Some(schema) => schema,
None => infer_json_schema_from_seekable(&mut buf_reader, self.max_records)?,
};
Ok(Reader::from_buf_reader(
buf_reader,
schema,
self.batch_size,
self.projection,
))
}
}
#[cfg(test)]
mod tests {
use crate::{
buffer::Buffer,
datatypes::DataType::{Dictionary, List},
};
use super::*;
use flate2::read::GzDecoder;
use std::fs::File;
use std::io::Cursor;
#[test]
fn test_json_basic() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(4, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(0, a.0);
assert_eq!(&DataType::Int64, a.1.data_type());
let b = schema.column_with_name("b").unwrap();
assert_eq!(1, b.0);
assert_eq!(&DataType::Float64, b.1.data_type());
let c = schema.column_with_name("c").unwrap();
assert_eq!(2, c.0);
assert_eq!(&DataType::Boolean, c.1.data_type());
let d = schema.column_with_name("d").unwrap();
assert_eq!(3, d.0);
assert_eq!(&DataType::Utf8, d.1.data_type());
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<Int64Array>()
.unwrap();
assert_eq!(1, aa.value(0));
assert_eq!(-10, aa.value(1));
let bb = batch
.column(b.0)
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
assert!(2.0 - bb.value(0) < f64::EPSILON);
assert!(-3.5 - bb.value(1) < f64::EPSILON);
let cc = batch
.column(c.0)
.as_any()
.downcast_ref::<BooleanArray>()
.unwrap();
assert_eq!(false, cc.value(0));
assert_eq!(true, cc.value(10));
let dd = batch
.column(d.0)
.as_any()
.downcast_ref::<StringArray>()
.unwrap();
assert_eq!("4", dd.value(0));
assert_eq!("text", dd.value(8));
}
#[test]
fn test_json_basic_with_nulls() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(4, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Int64, a.1.data_type());
let b = schema.column_with_name("b").unwrap();
assert_eq!(&DataType::Float64, b.1.data_type());
let c = schema.column_with_name("c").unwrap();
assert_eq!(&DataType::Boolean, c.1.data_type());
let d = schema.column_with_name("d").unwrap();
assert_eq!(&DataType::Utf8, d.1.data_type());
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<Int64Array>()
.unwrap();
assert_eq!(true, aa.is_valid(0));
assert_eq!(false, aa.is_valid(1));
assert_eq!(false, aa.is_valid(11));
let bb = batch
.column(b.0)
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
assert_eq!(true, bb.is_valid(0));
assert_eq!(false, bb.is_valid(2));
assert_eq!(false, bb.is_valid(11));
let cc = batch
.column(c.0)
.as_any()
.downcast_ref::<BooleanArray>()
.unwrap();
assert_eq!(true, cc.is_valid(0));
assert_eq!(false, cc.is_valid(4));
assert_eq!(false, cc.is_valid(11));
let dd = batch
.column(d.0)
.as_any()
.downcast_ref::<StringArray>()
.unwrap();
assert_eq!(false, dd.is_valid(0));
assert_eq!(true, dd.is_valid(1));
assert_eq!(false, dd.is_valid(4));
assert_eq!(false, dd.is_valid(11));
}
#[test]
fn test_json_basic_schema() {
let schema = Schema::new(vec![
Field::new("a", DataType::Int32, false),
Field::new("b", DataType::Float32, false),
Field::new("c", DataType::Boolean, false),
Field::new("d", DataType::Utf8, false),
]);
let mut reader: Reader<File> = Reader::new(
File::open("test/data/basic.json").unwrap(),
Arc::new(schema.clone()),
1024,
None,
);
let reader_schema = reader.schema();
assert_eq!(reader_schema, Arc::new(schema));
let batch = reader.next().unwrap().unwrap();
assert_eq!(4, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = batch.schema();
let a = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Int32, a.1.data_type());
let b = schema.column_with_name("b").unwrap();
assert_eq!(&DataType::Float32, b.1.data_type());
let c = schema.column_with_name("c").unwrap();
assert_eq!(&DataType::Boolean, c.1.data_type());
let d = schema.column_with_name("d").unwrap();
assert_eq!(&DataType::Utf8, d.1.data_type());
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<Int32Array>()
.unwrap();
assert_eq!(1, aa.value(0));
assert_eq!(false, aa.is_valid(11));
let bb = batch
.column(b.0)
.as_any()
.downcast_ref::<Float32Array>()
.unwrap();
assert!(2.0 - bb.value(0) < f32::EPSILON);
assert!(-3.5 - bb.value(1) < f32::EPSILON);
}
#[test]
fn test_json_basic_schema_projection() {
let schema = Schema::new(vec![
Field::new("a", DataType::Int32, false),
Field::new("b", DataType::Float32, false),
Field::new("c", DataType::Boolean, false),
]);
let mut reader: Reader<File> = Reader::new(
File::open("test/data/basic.json").unwrap(),
Arc::new(schema),
1024,
Some(vec!["a".to_string(), "c".to_string()]),
);
let reader_schema = reader.schema();
let expected_schema = Arc::new(Schema::new(vec![
Field::new("a", DataType::Int32, false),
Field::new("c", DataType::Boolean, false),
]));
assert_eq!(reader_schema, expected_schema);
let batch = reader.next().unwrap().unwrap();
assert_eq!(2, batch.num_columns());
assert_eq!(2, batch.schema().fields().len());
assert_eq!(12, batch.num_rows());
let schema = batch.schema();
assert_eq!(reader_schema, schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(0, a.0);
assert_eq!(&DataType::Int32, a.1.data_type());
let c = schema.column_with_name("c").unwrap();
assert_eq!(1, c.0);
assert_eq!(&DataType::Boolean, c.1.data_type());
}
#[test]
fn test_json_arrays() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/arrays.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(4, batch.num_columns());
assert_eq!(3, batch.num_rows());
let schema = batch.schema();
let a = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Int64, a.1.data_type());
let b = schema.column_with_name("b").unwrap();
assert_eq!(
&DataType::List(Box::new(Field::new("item", DataType::Float64, true))),
b.1.data_type()
);
let c = schema.column_with_name("c").unwrap();
assert_eq!(
&DataType::List(Box::new(Field::new("item", DataType::Boolean, true))),
c.1.data_type()
);
let d = schema.column_with_name("d").unwrap();
assert_eq!(&DataType::Utf8, d.1.data_type());
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<Int64Array>()
.unwrap();
assert_eq!(1, aa.value(0));
assert_eq!(-10, aa.value(1));
let bb = batch
.column(b.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let bb = bb.values();
let bb = bb.as_any().downcast_ref::<Float64Array>().unwrap();
assert_eq!(9, bb.len());
assert!(2.0 - bb.value(0) < f64::EPSILON);
assert!(-6.1 - bb.value(5) < f64::EPSILON);
assert_eq!(false, bb.is_valid(7));
let cc = batch
.column(c.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let cc = cc.values();
let cc = cc.as_any().downcast_ref::<BooleanArray>().unwrap();
assert_eq!(6, cc.len());
assert_eq!(false, cc.value(0));
assert_eq!(false, cc.value(4));
assert_eq!(false, cc.is_valid(5));
}
#[test]
fn test_invalid_json_infer_schema() {
let re = infer_json_schema_from_seekable(
&mut BufReader::new(
File::open("test/data/uk_cities_with_headers.csv").unwrap(),
),
None,
);
assert_eq!(
re.err().unwrap().to_string(),
"Json error: Not valid JSON: expected value at line 1 column 1",
);
}
#[test]
fn test_invalid_json_read_record() {
let schema = Arc::new(Schema::new(vec![Field::new(
"a",
DataType::Struct(vec![Field::new("a", DataType::Utf8, true)]),
true,
)]));
let builder = ReaderBuilder::new().with_schema(schema).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/uk_cities_with_headers.csv").unwrap())
.unwrap();
assert_eq!(
reader.next().err().unwrap().to_string(),
"Json error: Not valid JSON: expected value at line 1 column 1",
);
}
#[test]
fn test_coersion_scalar_and_list() {
use crate::datatypes::DataType::*;
assert_eq!(
List(Box::new(Field::new("item", Float64, true))),
coerce_data_type(vec![
&Float64,
&List(Box::new(Field::new("item", Float64, true)))
])
.unwrap()
);
assert_eq!(
List(Box::new(Field::new("item", Float64, true))),
coerce_data_type(vec![
&Float64,
&List(Box::new(Field::new("item", Int64, true)))
])
.unwrap()
);
assert_eq!(
List(Box::new(Field::new("item", Int64, true))),
coerce_data_type(vec![
&Int64,
&List(Box::new(Field::new("item", Int64, true)))
])
.unwrap()
);
assert_eq!(
List(Box::new(Field::new("item", Utf8, true))),
coerce_data_type(vec![
&Boolean,
&List(Box::new(Field::new("item", Float64, true)))
])
.unwrap()
);
}
#[test]
fn test_mixed_json_arrays() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/mixed_arrays.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
let mut file = File::open("test/data/mixed_arrays.json.gz").unwrap();
let mut reader = BufReader::new(GzDecoder::new(&file));
let schema = infer_json_schema(&mut reader, None).unwrap();
file.seek(SeekFrom::Start(0)).unwrap();
let reader = BufReader::new(GzDecoder::new(&file));
let mut reader = Reader::from_buf_reader(reader, schema, 64, None);
let batch_gz = reader.next().unwrap().unwrap();
for batch in vec![batch, batch_gz] {
assert_eq!(4, batch.num_columns());
assert_eq!(4, batch.num_rows());
let schema = batch.schema();
let a = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Int64, a.1.data_type());
let b = schema.column_with_name("b").unwrap();
assert_eq!(
&DataType::List(Box::new(Field::new("item", DataType::Float64, true))),
b.1.data_type()
);
let c = schema.column_with_name("c").unwrap();
assert_eq!(
&DataType::List(Box::new(Field::new("item", DataType::Boolean, true))),
c.1.data_type()
);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&DataType::List(Box::new(Field::new("item", DataType::Utf8, true))),
d.1.data_type()
);
let bb = batch
.column(b.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let bb = bb.values();
let bb = bb.as_any().downcast_ref::<Float64Array>().unwrap();
assert_eq!(10, bb.len());
assert!(4.0 - bb.value(9) < f64::EPSILON);
let cc = batch
.column(c.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
assert_eq!(
cc.data().buffers()[0],
Buffer::from(vec![0i32, 2, 2, 4, 5].to_byte_slice())
);
let cc = cc.values();
let cc = cc.as_any().downcast_ref::<BooleanArray>().unwrap();
let cc_expected = BooleanArray::from(vec![
Some(false),
Some(true),
Some(false),
None,
Some(false),
]);
assert_eq!(cc.data_ref(), cc_expected.data_ref());
let dd: &ListArray = batch
.column(d.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
assert_eq!(
dd.data().buffers()[0],
Buffer::from(vec![0i32, 1, 1, 2, 6].to_byte_slice())
);
let dd = dd.values();
let dd = dd.as_any().downcast_ref::<StringArray>().unwrap();
assert_eq!(6, dd.len());
assert_eq!("text", dd.value(1));
assert_eq!("1", dd.value(2));
assert_eq!("false", dd.value(3));
assert_eq!("array", dd.value(4));
assert_eq!("2.4", dd.value(5));
}
}
#[test]
fn test_nested_struct_json_arrays() {
let c_field = Field::new(
"c",
DataType::Struct(vec![Field::new("d", DataType::Utf8, true)]),
true,
);
let a_field = Field::new(
"a",
DataType::Struct(vec![
Field::new("b", DataType::Boolean, true),
c_field.clone(),
]),
true,
);
let schema = Arc::new(Schema::new(vec![a_field.clone()]));
let builder = ReaderBuilder::new().with_schema(schema).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/nested_structs.json").unwrap())
.unwrap();
let d = StringArray::from(vec![Some("text"), None, Some("text"), None]);
let c = ArrayDataBuilder::new(c_field.data_type().clone())
.len(4)
.add_child_data(d.data())
.null_bit_buffer(Buffer::from(vec![0b00000101]))
.build();
let b = BooleanArray::from(vec![Some(true), Some(false), Some(true), None]);
let a = ArrayDataBuilder::new(a_field.data_type().clone())
.len(4)
.add_child_data(b.data())
.add_child_data(c)
.null_bit_buffer(Buffer::from(vec![0b00000111]))
.build();
let expected = make_array(a);
let batch = reader.next().unwrap().unwrap();
let read = batch.column(0);
assert!(
expected.data_ref() == read.data_ref(),
format!("{:?} != {:?}", expected.data(), read.data())
);
}
#[test]
fn test_nested_list_json_arrays() {
let c_field = Field::new(
"c",
DataType::Struct(vec![Field::new("d", DataType::Utf8, true)]),
true,
);
let a_struct_field = Field::new(
"a",
DataType::Struct(vec![
Field::new("b", DataType::Boolean, true),
c_field.clone(),
]),
true,
);
let a_field =
Field::new("a", DataType::List(Box::new(a_struct_field.clone())), true);
let schema = Arc::new(Schema::new(vec![a_field.clone()]));
let builder = ReaderBuilder::new().with_schema(schema).with_batch_size(64);
let json_content = r#"
{"a": [{"b": true, "c": {"d": "a_text"}}, {"b": false, "c": {"d": "b_text"}}]}
{"a": [{"b": false, "c": null}]}
{"a": [{"b": true, "c": {"d": "c_text"}}, {"b": null, "c": {"d": "d_text"}}, {"b": true, "c": {"d": null}}]}
{"a": null}
{"a": []}
"#;
let mut reader = builder.build(Cursor::new(json_content)).unwrap();
let d = StringArray::from(vec![
Some("a_text"),
Some("b_text"),
None,
Some("c_text"),
Some("d_text"),
None,
None,
]);
let c = ArrayDataBuilder::new(c_field.data_type().clone())
.len(7)
.add_child_data(d.data())
.null_bit_buffer(Buffer::from(vec![0b00111011]))
.build();
let b = BooleanArray::from(vec![
Some(true),
Some(false),
Some(false),
Some(true),
None,
Some(true),
None,
]);
let a = ArrayDataBuilder::new(a_struct_field.data_type().clone())
.len(7)
.add_child_data(b.data())
.add_child_data(c.clone())
.null_bit_buffer(Buffer::from(vec![0b00111111]))
.build();
let a_list = ArrayDataBuilder::new(a_field.data_type().clone())
.len(5)
.add_buffer(Buffer::from(vec![0i32, 2, 3, 6, 6, 6].to_byte_slice()))
.add_child_data(a)
.null_bit_buffer(Buffer::from(vec![0b00010111]))
.build();
let expected = make_array(a_list);
let batch = reader.next().unwrap().unwrap();
let read = batch.column(0);
assert_eq!(read.len(), 5);
let read: &ListArray = read.as_any().downcast_ref::<ListArray>().unwrap();
let expected = expected.as_any().downcast_ref::<ListArray>().unwrap();
assert_eq!(
read.data().buffers()[0],
Buffer::from(vec![0i32, 2, 3, 6, 6, 6].to_byte_slice())
);
assert_eq!(read.data().null_buffer(), expected.data().null_buffer());
let struct_values = read.values();
let struct_array: &StructArray = struct_values
.as_any()
.downcast_ref::<StructArray>()
.unwrap();
let expected_struct_values = expected.values();
let expected_struct_array = expected_struct_values
.as_any()
.downcast_ref::<StructArray>()
.unwrap();
assert_eq!(7, struct_array.len());
assert_eq!(1, struct_array.null_count());
assert_eq!(7, expected_struct_array.len());
assert_eq!(1, expected_struct_array.null_count());
assert_eq!(
struct_array.data().null_buffer(),
expected_struct_array.data().null_buffer()
);
let read_b = struct_array.column(0);
assert_eq!(b.data_ref(), read_b.data_ref());
let read_c = struct_array.column(1);
assert_eq!(&c, read_c.data_ref());
let read_c: &StructArray = read_c.as_any().downcast_ref::<StructArray>().unwrap();
let read_d = read_c.column(0);
assert_eq!(d.data_ref(), read_d.data_ref());
assert_eq!(read.data_ref(), expected.data_ref());
}
#[test]
fn test_dictionary_from_json_basic_with_nulls() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::Int16), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::Int16), Box::new(DataType::Utf8)),
d.1.data_type()
);
let dd = batch
.column(d.0)
.as_any()
.downcast_ref::<DictionaryArray<Int16Type>>()
.unwrap();
assert_eq!(false, dd.is_valid(0));
assert_eq!(true, dd.is_valid(1));
assert_eq!(true, dd.is_valid(2));
assert_eq!(false, dd.is_valid(11));
assert_eq!(
dd.keys(),
&Int16Array::from(vec![
None,
Some(0),
Some(1),
Some(0),
None,
None,
Some(0),
None,
Some(1),
Some(0),
Some(0),
None
])
);
}
#[test]
fn test_dictionary_from_json_int8() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::Int8), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::Int8), Box::new(DataType::Utf8)),
d.1.data_type()
);
}
#[test]
fn test_dictionary_from_json_int32() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::Int32), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::Int32), Box::new(DataType::Utf8)),
d.1.data_type()
);
}
#[test]
fn test_dictionary_from_json_int64() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::Int64), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::Int64), Box::new(DataType::Utf8)),
d.1.data_type()
);
}
#[test]
fn test_skip_empty_lines() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let json_content = "
{\"a\": 1}
{\"a\": 2}
{\"a\": 3}";
let mut reader = builder.build(Cursor::new(json_content)).unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(3, batch.num_rows());
let schema = reader.schema();
let c = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Int64, c.1.data_type());
}
#[test]
fn test_row_type_validation() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let json_content = "
[1, \"hello\"]
\"world\"";
let re = builder.build(Cursor::new(json_content));
assert_eq!(
re.err().unwrap().to_string(),
r#"Json error: Expected JSON record to be an object, found Array([Number(1), String("hello")])"#,
);
}
#[test]
fn test_list_of_string_dictionary_from_json() {
let schema = Schema::new(vec![Field::new(
"events",
List(Box::new(Field::new(
"item",
Dictionary(Box::new(DataType::UInt64), Box::new(DataType::Utf8)),
true,
))),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/list_string_dict_nested.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(3, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let events = schema.column_with_name("events").unwrap();
assert_eq!(
&List(Box::new(Field::new(
"item",
Dictionary(Box::new(DataType::UInt64), Box::new(DataType::Utf8)),
true
))),
events.1.data_type()
);
let evs_list = batch
.column(events.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let evs_list = evs_list.values();
let evs_list = evs_list
.as_any()
.downcast_ref::<DictionaryArray<UInt64Type>>()
.unwrap();
assert_eq!(6, evs_list.len());
assert_eq!(true, evs_list.is_valid(1));
assert_eq!(DataType::Utf8, evs_list.value_type());
let dict_el = evs_list.values();
let dict_el = dict_el.as_any().downcast_ref::<StringArray>().unwrap();
assert_eq!(3, dict_el.len());
assert_eq!("Elect Leader", dict_el.value(0));
assert_eq!("Do Ballot", dict_el.value(1));
assert_eq!("Send Data", dict_el.value(2));
}
#[test]
fn test_list_of_string_dictionary_from_json_with_nulls() {
let schema = Schema::new(vec![Field::new(
"events",
List(Box::new(Field::new(
"item",
Dictionary(Box::new(DataType::UInt64), Box::new(DataType::Utf8)),
true,
))),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(
File::open("test/data/list_string_dict_nested_nulls.json").unwrap(),
)
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(3, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let events = schema.column_with_name("events").unwrap();
assert_eq!(
&List(Box::new(Field::new(
"item",
Dictionary(Box::new(DataType::UInt64), Box::new(DataType::Utf8)),
true
))),
events.1.data_type()
);
let evs_list = batch
.column(events.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let evs_list = evs_list.values();
let evs_list = evs_list
.as_any()
.downcast_ref::<DictionaryArray<UInt64Type>>()
.unwrap();
assert_eq!(8, evs_list.len());
assert_eq!(true, evs_list.is_valid(1));
assert_eq!(DataType::Utf8, evs_list.value_type());
let dict_el = evs_list.values();
let dict_el = dict_el.as_any().downcast_ref::<StringArray>().unwrap();
assert_eq!(2, evs_list.null_count());
assert_eq!(3, dict_el.len());
assert_eq!("Elect Leader", dict_el.value(0));
assert_eq!("Do Ballot", dict_el.value(1));
assert_eq!("Send Data", dict_el.value(2));
}
#[test]
fn test_dictionary_from_json_uint8() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::UInt8), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::UInt8), Box::new(DataType::Utf8)),
d.1.data_type()
);
}
#[test]
fn test_dictionary_from_json_uint32() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::UInt32), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::UInt32), Box::new(DataType::Utf8)),
d.1.data_type()
);
}
#[test]
fn test_dictionary_from_json_uint64() {
let schema = Schema::new(vec![Field::new(
"d",
Dictionary(Box::new(DataType::UInt64), Box::new(DataType::Utf8)),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let d = schema.column_with_name("d").unwrap();
assert_eq!(
&Dictionary(Box::new(DataType::UInt64), Box::new(DataType::Utf8)),
d.1.data_type()
);
}
#[test]
fn test_with_multiple_batches() {
let builder = ReaderBuilder::new()
.infer_schema(Some(4))
.with_batch_size(5);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let mut num_records = Vec::new();
while let Some(rb) = reader.next().unwrap() {
num_records.push(rb.num_rows());
}
assert_eq!(vec![5, 5, 2], num_records);
}
#[test]
fn test_json_infer_schema() {
let schema = Schema::new(vec![
Field::new("a", DataType::Int64, true),
Field::new(
"b",
DataType::List(Box::new(Field::new("item", DataType::Float64, true))),
true,
),
Field::new(
"c",
DataType::List(Box::new(Field::new("item", DataType::Boolean, true))),
true,
),
Field::new(
"d",
DataType::List(Box::new(Field::new("item", DataType::Utf8, true))),
true,
),
]);
let mut reader =
BufReader::new(File::open("test/data/mixed_arrays.json").unwrap());
let inferred_schema = infer_json_schema_from_seekable(&mut reader, None).unwrap();
assert_eq!(inferred_schema, Arc::new(schema.clone()));
let file = File::open("test/data/mixed_arrays.json.gz").unwrap();
let mut reader = BufReader::new(GzDecoder::new(&file));
let inferred_schema = infer_json_schema(&mut reader, None).unwrap();
assert_eq!(inferred_schema, Arc::new(schema));
}
#[test]
fn test_timestamp_from_json_seconds() {
let schema = Schema::new(vec![Field::new(
"a",
DataType::Timestamp(TimeUnit::Second, None),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(
&DataType::Timestamp(TimeUnit::Second, None),
a.1.data_type()
);
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<TimestampSecondArray>()
.unwrap();
assert_eq!(true, aa.is_valid(0));
assert_eq!(false, aa.is_valid(1));
assert_eq!(false, aa.is_valid(2));
assert_eq!(1, aa.value(0));
assert_eq!(1, aa.value(3));
assert_eq!(5, aa.value(7));
}
#[test]
fn test_timestamp_from_json_milliseconds() {
let schema = Schema::new(vec![Field::new(
"a",
DataType::Timestamp(TimeUnit::Millisecond, None),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(
&DataType::Timestamp(TimeUnit::Millisecond, None),
a.1.data_type()
);
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<TimestampMillisecondArray>()
.unwrap();
assert_eq!(true, aa.is_valid(0));
assert_eq!(false, aa.is_valid(1));
assert_eq!(false, aa.is_valid(2));
assert_eq!(1, aa.value(0));
assert_eq!(1, aa.value(3));
assert_eq!(5, aa.value(7));
}
#[test]
fn test_date_from_json_milliseconds() {
let schema = Schema::new(vec![Field::new(
"a",
DataType::Date64(DateUnit::Millisecond),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Date64(DateUnit::Millisecond), a.1.data_type());
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<Date64Array>()
.unwrap();
assert_eq!(true, aa.is_valid(0));
assert_eq!(false, aa.is_valid(1));
assert_eq!(false, aa.is_valid(2));
assert_eq!(1, aa.value(0));
assert_eq!(1, aa.value(3));
assert_eq!(5, aa.value(7));
}
#[test]
fn test_time_from_json_nanoseconds() {
let schema = Schema::new(vec![Field::new(
"a",
DataType::Time64(TimeUnit::Nanosecond),
true,
)]);
let builder = ReaderBuilder::new()
.with_schema(Arc::new(schema))
.with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/basic_nulls.json").unwrap())
.unwrap();
let batch = reader.next().unwrap().unwrap();
assert_eq!(1, batch.num_columns());
assert_eq!(12, batch.num_rows());
let schema = reader.schema();
let batch_schema = batch.schema();
assert_eq!(schema, batch_schema);
let a = schema.column_with_name("a").unwrap();
assert_eq!(&DataType::Time64(TimeUnit::Nanosecond), a.1.data_type());
let aa = batch
.column(a.0)
.as_any()
.downcast_ref::<Time64NanosecondArray>()
.unwrap();
assert_eq!(true, aa.is_valid(0));
assert_eq!(false, aa.is_valid(1));
assert_eq!(false, aa.is_valid(2));
assert_eq!(1, aa.value(0));
assert_eq!(1, aa.value(3));
assert_eq!(5, aa.value(7));
}
}