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feat: Add support for Utf8Type and TimeStamp in Parquet statistics #9129

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feat: Add support for Utf8Type and TimeStamp in Parquet statistics #9129

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86cf9a6
Refactor parquet.rs: Add support for Utf8Type and ByteArray statistics
Weijun-H Feb 4, 2024
e4175e0
support timestamp stat in row group
Weijun-H Feb 5, 2024
2d6abca
Suppot TimeStamp for Parquet Statistics
Weijun-H Feb 5, 2024
b792e0f
Fix timestamp conversion bug in Parquet row_groups.rs and statistics.rs
Weijun-H Feb 7, 2024
4c05c91
fix fmt and clippy
Weijun-H Feb 7, 2024
6c41090
Add row group pruning tests for different timestamp units
Weijun-H Feb 7, 2024
2192cf5
Update ParquetTimeUnit import
Weijun-H Feb 7, 2024
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130 changes: 119 additions & 11 deletions datafusion/core/src/datasource/file_format/parquet.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,12 @@

//! [`ParquetFormat`]: Parquet [`FileFormat`] abstractions

use arrow_array::RecordBatch;
use arrow_array::types::Utf8Type;
use arrow_array::{
GenericByteArray, RecordBatch, TimestampMicrosecondArray, TimestampMillisecondArray,
TimestampNanosecondArray, TimestampSecondArray,
};
use arrow_schema::TimeUnit;
use async_trait::async_trait;
use datafusion_common::stats::Precision;
use datafusion_physical_plan::metrics::MetricsSet;
Expand Down Expand Up @@ -333,18 +338,98 @@ fn summarize_min_max(
.unwrap_or_else(|_| min_values[i] = None);
}
}
ParquetStatistics::Int64(s) if DataType::Int64 == *fields[i].data_type() => {
if let Some(max_value) = &mut max_values[i] {
max_value
.update_batch(&[Arc::new(Int64Array::from_value(*s.max(), 1))])
.unwrap_or_else(|_| max_values[i] = None);
ParquetStatistics::Int64(s) => match fields[i].data_type().clone() {
DataType::Int64 => {
if let Some(max_value) = &mut max_values[i] {
max_value
.update_batch(&[Arc::new(Int64Array::from_value(*s.max(), 1))])
.unwrap_or_else(|_| max_values[i] = None);
}
if let Some(min_value) = &mut min_values[i] {
min_value
.update_batch(&[Arc::new(Int64Array::from_value(*s.min(), 1))])
.unwrap_or_else(|_| min_values[i] = None);
}
}
if let Some(min_value) = &mut min_values[i] {
min_value
.update_batch(&[Arc::new(Int64Array::from_value(*s.min(), 1))])
.unwrap_or_else(|_| min_values[i] = None);
DataType::Timestamp(time_unit, time_zone) => match time_unit {
TimeUnit::Second => {
if let Some(max_value) = &mut max_values[i] {
max_value
.update_batch(&[Arc::new(
TimestampSecondArray::from_value(*s.max(), 1)
.with_timezone_opt(time_zone.clone()),
)])
.unwrap_or_else(|_| max_values[i] = None);
}
if let Some(min_value) = &mut min_values[i] {
min_value
.update_batch(&[Arc::new(
TimestampSecondArray::from_value(*s.min(), 1)
.with_timezone_opt(time_zone),
)])
.unwrap_or_else(|_| min_values[i] = None);
}
}
TimeUnit::Millisecond => {
if let Some(max_value) = &mut max_values[i] {
max_value
.update_batch(&[Arc::new(
TimestampMillisecondArray::from_value(*s.max(), 1)
.with_timezone_opt(time_zone.clone()),
)])
.unwrap_or_else(|_| max_values[i] = None);
}
if let Some(min_value) = &mut min_values[i] {
min_value
.update_batch(&[Arc::new(
TimestampMillisecondArray::from_value(*s.min(), 1)
.with_timezone_opt(time_zone),
)])
.unwrap_or_else(|_| min_values[i] = None);
}
}
TimeUnit::Microsecond => {
if let Some(max_value) = &mut max_values[i] {
max_value
.update_batch(&[Arc::new(
TimestampMicrosecondArray::from_value(*s.max(), 1)
.with_timezone_opt(time_zone.clone()),
)])
.unwrap_or_else(|_| max_values[i] = None);
}
if let Some(min_value) = &mut min_values[i] {
min_value
.update_batch(&[Arc::new(
TimestampMicrosecondArray::from_value(*s.min(), 1)
.with_timezone_opt(time_zone),
)])
.unwrap_or_else(|_| min_values[i] = None);
}
}
TimeUnit::Nanosecond => {
if let Some(max_value) = &mut max_values[i] {
max_value
.update_batch(&[Arc::new(
TimestampNanosecondArray::from_value(*s.max(), 1)
.with_timezone_opt(time_zone.clone()),
)])
.unwrap_or_else(|_| max_values[i] = None);
}
if let Some(min_value) = &mut min_values[i] {
min_value
.update_batch(&[Arc::new(
TimestampNanosecondArray::from_value(*s.min(), 1)
.with_timezone_opt(time_zone),
)])
.unwrap_or_else(|_| min_values[i] = None);
}
}
},
_ => {
max_values[i] = None;
min_values[i] = None;
}
}
},
ParquetStatistics::Float(s) if DataType::Float32 == *fields[i].data_type() => {
if let Some(max_value) = &mut max_values[i] {
max_value
Expand All @@ -369,6 +454,29 @@ fn summarize_min_max(
.unwrap_or_else(|_| min_values[i] = None);
}
}

ParquetStatistics::ByteArray(s)
if matches!(fields[i].data_type(), DataType::Utf8 | DataType::LargeUtf8) =>
{
if let Some(max_value) = &mut max_values[i] {
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I believe byte arrays are also used to store DataType::Decimal values as well (though hopefully if we consolidate the statistics conversion code it will "just work")

let stat_value = s.max().as_utf8().unwrap_or_default();
let array: GenericByteArray<Utf8Type> = vec![Some(stat_value)].into();
if max_value.update_batch(&[Arc::new(array)]).is_err()
|| stat_value.is_empty()
{
max_values[i] = None;
}
}
if let Some(min_value) = &mut min_values[i] {
let stat_value = s.min().as_utf8().unwrap_or_default();
let array: GenericByteArray<Utf8Type> = vec![Some(stat_value)].into();
if min_value.update_batch(&[Arc::new(array)]).is_err()
|| stat_value.is_empty()
{
min_values[i] = None;
}
}
}
_ => {
max_values[i] = None;
min_values[i] = None;
Expand Down
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