use indexmap::map::IndexMap as HashMap;
use indexmap::set::IndexSet as HashSet;
use std::io::{BufRead, BufReader, Read, Seek, SeekFrom};
use std::sync::Arc;
use serde_json::Value;
use crate::array::*;
use crate::datatypes::*;
use crate::error::{ArrowError, Result};
use crate::record_batch::RecordBatch;
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(DataType::Float64)))
|| dt.contains(&&DataType::List(Box::new(DataType::Int64)))
|| dt.contains(&&DataType::List(Box::new(DataType::Boolean)))
|| dt.contains(&&DataType::List(Box::new(DataType::Utf8)))
{
let mut dt = dt;
dt.sort();
match (dt[0], dt[1]) {
(t1, DataType::List(e)) if **e == DataType::Float64 => {
if t1 == &DataType::Float64 {
Ok(DataType::List(Box::new(DataType::Float64)))
} else {
Ok(DataType::List(Box::new(coerce_data_type(vec![
t1,
&DataType::Float64,
])?)))
}
}
(t1, DataType::List(e)) if **e == DataType::Int64 => {
if t1 == &DataType::Int64 {
Ok(DataType::List(Box::new(DataType::Int64)))
} else {
Ok(DataType::List(Box::new(coerce_data_type(vec![
t1,
&DataType::Int64,
])?)))
}
}
(t1, DataType::List(e)) if **e == DataType::Boolean => {
if t1 == &DataType::Boolean {
Ok(DataType::List(Box::new(DataType::Boolean)))
} else {
Ok(DataType::List(Box::new(coerce_data_type(vec![
t1,
&DataType::Boolean,
])?)))
}
}
(t1, DataType::List(e)) if **e == DataType::Utf8 => {
if t1 == &DataType::Utf8 {
Ok(DataType::List(Box::new(DataType::Utf8)))
} else {
dbg!(&t1);
Ok(DataType::List(Box::new(coerce_data_type(vec![
t1,
&DataType::Utf8,
])?)))
}
}
(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(DataType::Utf8)))
}
}
}
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),
}
}
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> {
let mut values: HashMap<String, HashSet<DataType>> = HashMap::new();
let mut line = String::new();
for _ in 0..max_read_records.unwrap_or(std::usize::MAX) {
reader.read_line(&mut line)?;
if line.is_empty() {
break;
}
let record: Value = serde_json::from_str(&line.trim()).expect("Not valid JSON");
line = String::new();
match record {
Value::Object(map) => {
let res = map
.iter()
.map(|(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(dt)));
} else {
let mut hs = HashSet::new();
hs.insert(DataType::List(Box::new(dt)));
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(
"Reading nested JSON structs currently not supported"
.to_string(),
)),
}
})
.collect();
match res {
Ok(()) => {}
Err(e) => return Err(e),
}
}
t => {
return Err(ArrowError::JsonError(format!(
"Expected JSON record to be an object, found {:?}",
t
)));
}
};
}
generate_schema(values)
}
#[derive(Debug)]
pub struct Reader<R: Read> {
schema: SchemaRef,
projection: Option<Vec<String>>,
reader: BufReader<R>,
batch_size: usize,
}
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 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 from_buf_reader(
reader: BufReader<R>,
schema: SchemaRef,
batch_size: usize,
projection: Option<Vec<String>>,
) -> Self {
Self {
schema,
projection,
reader,
batch_size,
}
}
#[allow(clippy::should_implement_trait)]
pub fn next(&mut self) -> Result<Option<RecordBatch>> {
let mut rows: Vec<Value> = Vec::with_capacity(self.batch_size);
let mut line = String::new();
for _ in 0..self.batch_size {
let bytes_read = self.reader.read_line(&mut line)?;
if bytes_read > 0 {
rows.push(serde_json::from_str(&line).expect("Not valid JSON"));
line = String::new();
} else {
break;
}
}
if rows.is_empty() {
return Ok(None);
}
let rows = &rows[..];
let projection = self.projection.clone().unwrap_or_else(Vec::new);
let arrays: Result<Vec<ArrayRef>> = self
.schema
.clone()
.fields()
.iter()
.filter(|field| {
if projection.is_empty() {
return true;
}
projection.contains(field.name())
})
.map(|field| {
match field.data_type().clone() {
DataType::Null => unimplemented!(),
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::Utf8 => {
let mut builder = StringBuilder::new(rows.len());
for row in rows {
if let Some(value) = row.get(field.name()) {
if let Some(str_v) = value.as_str() {
builder.append_value(str_v)?
} else {
builder.append(false)?
}
} else {
builder.append(false)?
}
}
Ok(Arc::new(builder.finish()) as ArrayRef)
}
DataType::List(ref t) => match **t {
DataType::Int8 => self.build_list_array::<Int8Type>(rows, field.name()),
DataType::Int16 => self.build_list_array::<Int16Type>(rows, field.name()),
DataType::Int32 => self.build_list_array::<Int32Type>(rows, field.name()),
DataType::Int64 => self.build_list_array::<Int64Type>(rows, field.name()),
DataType::UInt8 => self.build_list_array::<UInt8Type>(rows, field.name()),
DataType::UInt16 => self.build_list_array::<UInt16Type>(rows, field.name()),
DataType::UInt32 => self.build_list_array::<UInt32Type>(rows, field.name()),
DataType::UInt64 => self.build_list_array::<UInt64Type>(rows, field.name()),
DataType::Float32 => self.build_list_array::<Float32Type>(rows, field.name()),
DataType::Float64 => self.build_list_array::<Float64Type>(rows, field.name()),
DataType::Null => unimplemented!(),
DataType::Boolean => self.build_boolean_list_array(rows, field.name()),
DataType::Utf8 => {
let values_builder = StringBuilder::new(rows.len() * 5);
let mut builder = ListBuilder::new(values_builder);
for row in rows {
if let Some(value) = row.get(field.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() {
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()));
};
for val in vals {
if let Some(v) = val {
builder.values().append_value(&v)?
} else {
builder.values().append_null()?
};
}
}
builder.append(true)?
}
Ok(Arc::new(builder.finish()) as ArrayRef)
}
_ => Err(ArrowError::JsonError("Data type is currently not supported in a list".to_string())),
},
DataType::Dictionary(ref key_typ, ref value_type) => {
if let DataType::Utf8 = **value_type {
match **key_typ {
DataType::Int8 => self.build_dictionary_array::<Int8Type>(rows, field.name()),
DataType::Int16 => self.build_dictionary_array::<Int16Type>(rows, field.name()),
DataType::Int32 => self.build_dictionary_array::<Int32Type>(rows, field.name()),
DataType::Int64 => self.build_dictionary_array::<Int64Type>(rows, field.name()),
DataType::UInt8 => self.build_dictionary_array::<UInt8Type>(rows, field.name()),
DataType::UInt16 => self.build_dictionary_array::<UInt16Type>(rows, field.name()),
DataType::UInt32 => self.build_dictionary_array::<UInt32Type>(rows, field.name()),
DataType::UInt64 => self.build_dictionary_array::<UInt64Type>(rows, field.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()))
}
}
_ => Err(ArrowError::JsonError("struct types are not yet supported".to_string())),
}
})
.collect();
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_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_boolean_list_array(
&self,
rows: &[Value],
col_name: &str,
) -> Result<ArrayRef> {
let values_builder = BooleanBuilder::new(rows.len() * 5);
let mut builder = ListBuilder::new(values_builder);
for row in rows {
if let Some(value) = row.get(col_name) {
let vals: Vec<Option<bool>> = if let Value::Bool(v) = value {
vec![Some(*v)]
} else if let Value::Array(n) = value {
n.iter().map(|v: &Value| v.as_bool()).collect()
} else if let Value::Null = value {
vec![None]
} else {
return Err(ArrowError::JsonError(
"2Only scalars are currently supported in JSON arrays"
.to_string(),
));
};
for val in vals {
match val {
Some(v) => builder.values().append_value(v)?,
None => builder.values().append_null()?,
};
}
}
builder.append(true)?
}
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,
{
let mut builder = PrimitiveBuilder::<T>::new(rows.len());
for row in rows {
if let Some(value) = row.get(&col_name) {
match value.as_f64() {
Some(v) => match num::cast::cast(v) {
Some(v) => builder.append_value(v)?,
None => builder.append_null()?,
},
None => builder.append_null()?,
}
} else {
builder.append_null()?;
}
}
Ok(Arc::new(builder.finish()))
}
fn build_list_array<T: ArrowPrimitiveType>(
&self,
rows: &[Value],
col_name: &str,
) -> Result<ArrayRef>
where
T::Native: num::NumCast,
{
let values_builder: PrimitiveBuilder<T> = PrimitiveBuilder::new(rows.len());
let mut builder = ListBuilder::new(values_builder);
for row in rows {
if let Some(value) = row.get(&col_name) {
let vals: Vec<Option<f64>> = if let Value::Number(value) = value {
vec![value.as_f64()]
} else if let Value::Array(n) = value {
n.iter().map(|v: &Value| v.as_f64()).collect()
} else if let Value::Null = value {
vec![None]
} else {
return Err(ArrowError::JsonError(
"3Only scalars are currently supported in JSON arrays"
.to_string(),
));
};
for val in vals {
match val {
Some(v) => match num::cast::cast(v) {
Some(v) => builder.values().append_value(v)?,
None => builder.values().append_null()?,
},
None => builder.values().append_null()?,
};
}
}
builder.append(true)?
}
Ok(Arc::new(builder.finish()))
}
fn build_dictionary_array<T: ArrowPrimitiveType>(
&self,
rows: &[Value],
col_name: &str,
) -> Result<ArrayRef>
where
T::Native: num::NumCast,
T: ArrowDictionaryKeyType,
{
let key_builder = PrimitiveBuilder::<T>::new(rows.len());
let value_builder = StringBuilder::new(100);
let mut builder = StringDictionaryBuilder::new(key_builder, value_builder);
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)
}
}
#[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: Read + Seek>(self, source: R) -> Result<Reader<R>> {
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::datatypes::DataType::Dictionary;
use super::*;
use flate2::read::GzDecoder;
use std::fs::File;
#[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_eq!(2.0, bb.value(0));
assert_eq!(-3.5, bb.value(1));
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_eq!(2.0, bb.value(0));
assert_eq!(-3.5, bb.value(1));
}
#[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.clone(), 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(DataType::Float64)),
b.1.data_type()
);
let c = schema.column_with_name("c").unwrap();
assert_eq!(
&DataType::List(Box::new(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!(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_eq!(2.0, bb.value(0));
assert_eq!(-6.1, bb.value(5));
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]
#[should_panic(expected = "Not valid JSON")]
fn test_invalid_file() {
let builder = ReaderBuilder::new().infer_schema(None).with_batch_size(64);
let mut reader: Reader<File> = builder
.build::<File>(File::open("test/data/uk_cities_with_headers.csv").unwrap())
.unwrap();
let _batch = reader.next().unwrap().unwrap();
}
#[test]
fn test_coersion_scalar_and_list() {
use crate::datatypes::DataType::*;
assert_eq!(
List(Box::new(Float64)),
coerce_data_type(vec![&Float64, &List(Box::new(Float64))]).unwrap()
);
assert_eq!(
List(Box::new(Float64)),
coerce_data_type(vec![&Float64, &List(Box::new(Int64))]).unwrap()
);
assert_eq!(
List(Box::new(Int64)),
coerce_data_type(vec![&Int64, &List(Box::new(Int64))]).unwrap()
);
assert_eq!(
List(Box::new(Utf8)),
coerce_data_type(vec![&Boolean, &List(Box::new(Float64))]).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(DataType::Float64)),
b.1.data_type()
);
let c = schema.column_with_name("c").unwrap();
assert_eq!(
&DataType::List(Box::new(DataType::Boolean)),
c.1.data_type()
);
let d = schema.column_with_name("d").unwrap();
assert_eq!(&DataType::List(Box::new(DataType::Utf8)), 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_eq!(4.0, bb.value(9));
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(3));
assert_eq!(false, cc.is_valid(2));
assert_eq!(false, cc.is_valid(4));
let dd = batch
.column(d.0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let dd = dd.values();
let dd = dd.as_any().downcast_ref::<StringArray>().unwrap();
assert_eq!(7, dd.len());
assert_eq!(false, dd.is_valid(1));
assert_eq!("text", dd.value(2));
assert_eq!("1", dd.value(3));
assert_eq!("false", dd.value(4));
assert_eq!("array", dd.value(5));
assert_eq!("2.4", dd.value(6));
}
}
#[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));
let keys: Vec<_> = dd.keys().collect();
assert_eq!(
keys,
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_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(DataType::Float64)), true),
Field::new("c", DataType::List(Box::new(DataType::Boolean)), true),
Field::new("d", DataType::List(Box::new(DataType::Utf8)), 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));
}
}