Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Minor: Add new bloom filter predicate tests #8433

Merged
merged 2 commits into from
Dec 8, 2023
Merged

Minor: Add new bloom filter predicate tests #8433

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
415c2ce
Minor: Add new bloom filter tests
alamb Dec 6, 2023
e5b30eb
fmt
alamb Dec 6, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
117 changes: 113 additions & 4 deletions datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -350,6 +350,7 @@ mod tests {
use arrow::datatypes::Schema;
use arrow::datatypes::{DataType, Field};
use datafusion_common::{config::ConfigOptions, TableReference, ToDFSchema};
use datafusion_common::{DataFusionError, Result};
use datafusion_expr::{
builder::LogicalTableSource, cast, col, lit, AggregateUDF, Expr, ScalarUDF,
TableSource, WindowUDF,
Expand Down Expand Up @@ -994,6 +995,26 @@ mod tests {
create_physical_expr(expr, &df_schema, schema, &execution_props).unwrap()
}

// Note the values in the `String` column are:
// ❯ select * from './parquet-testing/data/data_index_bloom_encoding_stats.parquet';
// +-----------+
// | String |
// +-----------+
// | Hello |
// | This is |
// | a |
// | test |
// | How |
// | are you |
// | doing |
// | today |
// | the quick |
// | brown fox |
// | jumps |
// | over |
// | the lazy |
// | dog |
// +-----------+
#[tokio::test]
async fn test_row_group_bloom_filter_pruning_predicate_simple_expr() {
// load parquet file
Expand All @@ -1002,7 +1023,7 @@ mod tests {
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate
// generate pruning predicate `(String = "Hello_Not_exists")`
let schema = Schema::new(vec![Field::new("String", DataType::Utf8, false)]);
let expr = col(r#""String""#).eq(lit("Hello_Not_Exists"));
let expr = logical2physical(&expr, &schema);
Expand All @@ -1029,7 +1050,7 @@ mod tests {
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate
// generate pruning predicate `(String = "Hello_Not_exists" OR String = "Hello_Not_exists2")`
let schema = Schema::new(vec![Field::new("String", DataType::Utf8, false)]);
let expr = lit("1").eq(lit("1")).and(
col(r#""String""#)
Expand Down Expand Up @@ -1091,7 +1112,7 @@ mod tests {
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate
// generate pruning predicate `(String = "Hello")`
let schema = Schema::new(vec![Field::new("String", DataType::Utf8, false)]);
let expr = col(r#""String""#).eq(lit("Hello"));
let expr = logical2physical(&expr, &schema);
Expand All @@ -1110,6 +1131,94 @@ mod tests {
assert_eq!(pruned_row_groups, row_groups);
}

#[tokio::test]
async fn test_row_group_bloom_filter_pruning_predicate_with_exists_2_values() {
// load parquet file
let testdata = datafusion_common::test_util::parquet_test_data();
let file_name = "data_index_bloom_encoding_stats.parquet";
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate `(String = "Hello") OR (String = "the quick")`
let schema = Schema::new(vec![Field::new("String", DataType::Utf8, false)]);
let expr = col(r#""String""#)
.eq(lit("Hello"))
.or(col(r#""String""#).eq(lit("the quick")));
let expr = logical2physical(&expr, &schema);
let pruning_predicate =
PruningPredicate::try_new(expr, Arc::new(schema)).unwrap();

let row_groups = vec![0];
let pruned_row_groups = test_row_group_bloom_filter_pruning_predicate(
file_name,
data,
&pruning_predicate,
&row_groups,
)
.await
.unwrap();
assert_eq!(pruned_row_groups, row_groups);
}

#[tokio::test]
async fn test_row_group_bloom_filter_pruning_predicate_with_exists_3_values() {
// load parquet file
let testdata = datafusion_common::test_util::parquet_test_data();
let file_name = "data_index_bloom_encoding_stats.parquet";
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate `(String = "Hello") OR (String = "the quick") OR (String = "are you")`
let schema = Schema::new(vec![Field::new("String", DataType::Utf8, false)]);
let expr = col(r#""String""#)
.eq(lit("Hello"))
.or(col(r#""String""#).eq(lit("the quick")))
.or(col(r#""String""#).eq(lit("are you")));
let expr = logical2physical(&expr, &schema);
let pruning_predicate =
PruningPredicate::try_new(expr, Arc::new(schema)).unwrap();

let row_groups = vec![0];
let pruned_row_groups = test_row_group_bloom_filter_pruning_predicate(
file_name,
data,
&pruning_predicate,
&row_groups,
)
.await
.unwrap();
assert_eq!(pruned_row_groups, row_groups);
}

#[tokio::test]
async fn test_row_group_bloom_filter_pruning_predicate_with_or_not_eq() {
// load parquet file
let testdata = datafusion_common::test_util::parquet_test_data();
let file_name = "data_index_bloom_encoding_stats.parquet";
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate `(String = "foo") OR (String != "bar")`
let schema = Schema::new(vec![Field::new("String", DataType::Utf8, false)]);
let expr = col(r#""String""#)
.not_eq(lit("foo"))
.or(col(r#""String""#).not_eq(lit("bar")));
let expr = logical2physical(&expr, &schema);
let pruning_predicate =
PruningPredicate::try_new(expr, Arc::new(schema)).unwrap();

let row_groups = vec![0];
let pruned_row_groups = test_row_group_bloom_filter_pruning_predicate(
file_name,
data,
&pruning_predicate,
&row_groups,
)
.await
.unwrap();
assert_eq!(pruned_row_groups, row_groups);
}

#[tokio::test]
async fn test_row_group_bloom_filter_pruning_predicate_without_bloom_filter() {
// load parquet file
Expand All @@ -1118,7 +1227,7 @@ mod tests {
let path = format!("{testdata}/{file_name}");
let data = bytes::Bytes::from(std::fs::read(path).unwrap());

// generate pruning predicate
// generate pruning predicate on a column without a bloom filter
let schema = Schema::new(vec![Field::new("string_col", DataType::Utf8, false)]);
let expr = col(r#""string_col""#).eq(lit("0"));
let expr = logical2physical(&expr, &schema);
Expand Down