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datafusion_test.rs
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datafusion_test.rs
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#![cfg(feature = "datafusion")]
use std::collections::HashSet;
use std::path::PathBuf;
use std::sync::Arc;
use arrow::array::*;
use arrow::datatypes::{DataType as ArrowDataType, Field as ArrowField, Schema as ArrowSchema};
use arrow::record_batch::RecordBatch;
use common::datafusion::context_with_delta_table_factory;
use datafusion::assert_batches_sorted_eq;
use datafusion::datasource::TableProvider;
use datafusion::execution::context::{SessionContext, TaskContext};
use datafusion::physical_plan::coalesce_partitions::CoalescePartitionsExec;
use datafusion::physical_plan::{common::collect, file_format::ParquetExec, metrics::Label};
use datafusion::physical_plan::{visit_execution_plan, ExecutionPlan, ExecutionPlanVisitor};
use datafusion_common::scalar::ScalarValue;
use datafusion_common::{Column, DataFusionError, Result};
use datafusion_expr::Expr;
use deltalake::action::SaveMode;
use deltalake::operations::create::CreateBuilder;
use deltalake::{
operations::{write::WriteBuilder, DeltaOps},
DeltaTable, Schema,
};
mod common;
fn get_scanned_files(node: &dyn ExecutionPlan) -> HashSet<Label> {
node.metrics()
.unwrap()
.iter()
.flat_map(|m| m.labels().to_vec())
.collect()
}
#[derive(Debug, Default)]
pub struct ExecutionMetricsCollector {
scanned_files: HashSet<Label>,
}
impl ExecutionMetricsCollector {
fn num_scanned_files(&self) -> usize {
self.scanned_files.len()
}
}
impl ExecutionPlanVisitor for ExecutionMetricsCollector {
type Error = DataFusionError;
fn pre_visit(&mut self, plan: &dyn ExecutionPlan) -> std::result::Result<bool, Self::Error> {
if let Some(exec) = plan.as_any().downcast_ref::<ParquetExec>() {
let files = get_scanned_files(exec);
self.scanned_files.extend(files);
}
Ok(true)
}
}
async fn prepare_table(
batches: Vec<RecordBatch>,
save_mode: SaveMode,
) -> (tempfile::TempDir, Arc<DeltaTable>) {
let table_dir = tempfile::tempdir().unwrap();
let table_path = table_dir.path();
let table_uri = table_path.to_str().unwrap().to_string();
let table_schema: Schema = batches[0].schema().try_into().unwrap();
let mut table = DeltaOps::try_from_uri(table_uri)
.await
.unwrap()
.create()
.with_save_mode(SaveMode::Ignore)
.with_columns(table_schema.get_fields().clone())
.await
.unwrap();
for batch in batches {
table = DeltaOps(table)
.write(vec![batch])
.with_save_mode(save_mode.clone())
.await
.unwrap();
}
(table_dir, Arc::new(table))
}
#[tokio::test]
async fn test_datafusion_sql_registration() -> Result<()> {
let ctx = context_with_delta_table_factory();
let mut d = PathBuf::from(env!("CARGO_MANIFEST_DIR"));
d.push("tests/data/delta-0.8.0-partitioned");
let sql = format!(
"CREATE EXTERNAL TABLE demo STORED AS DELTATABLE LOCATION '{}'",
d.to_str().unwrap()
);
let _ = ctx
.sql(sql.as_str())
.await
.expect("Failed to register table!");
let batches = ctx
.sql("SELECT CAST( day as int ) as my_day FROM demo WHERE CAST( year as int ) > 2020 ORDER BY CAST( day as int ) ASC")
.await?
.collect()
.await?;
let batch = &batches[0];
assert_eq!(
batch.column(0).as_ref(),
Arc::new(Int32Array::from(vec![4, 5, 20, 20])).as_ref(),
);
Ok(())
}
#[tokio::test]
async fn test_datafusion_simple_query_partitioned() -> Result<()> {
let ctx = SessionContext::new();
let table = deltalake::open_table("./tests/data/delta-0.8.0-partitioned")
.await
.unwrap();
ctx.register_table("demo", Arc::new(table))?;
let batches = ctx
.sql("SELECT CAST( day as int ) as my_day FROM demo WHERE CAST( year as int ) > 2020 ORDER BY CAST( day as int ) ASC")
.await?
.collect()
.await?;
let batch = &batches[0];
assert_eq!(
batch.column(0).as_ref(),
Arc::new(Int32Array::from(vec![4, 5, 20, 20])).as_ref(),
);
Ok(())
}
#[tokio::test]
async fn test_datafusion_write_from_delta_scan() -> Result<()> {
let ctx = SessionContext::new();
let state = ctx.state();
// Build an execution plan for scanning a DeltaTable
let source_table = deltalake::open_table("./tests/data/delta-0.8.0-date").await?;
let source_scan = source_table.scan(&state, None, &[], None).await?;
// Create target Delta Table
let target_table = CreateBuilder::new()
.with_location("memory://target")
.with_columns(source_table.schema().unwrap().get_fields().clone())
.with_table_name("target")
.await?;
// Trying to execute the write by providing only the Datafusion plan and not the session state
// results in an error due to missing object store in the runtime registry.
assert!(WriteBuilder::new()
.with_input_execution_plan(source_scan.clone())
.with_object_store(target_table.object_store())
.await
.unwrap_err()
.to_string()
.contains("No suitable object store found for delta-rs://"));
// Execute write to the target table with the proper state
let target_table = WriteBuilder::new()
.with_input_execution_plan(source_scan)
.with_input_session_state(state)
.with_object_store(target_table.object_store())
.await?;
ctx.register_table("target", Arc::new(target_table))?;
let batches = ctx.sql("SELECT * FROM target").await?.collect().await?;
let expected = vec![
"+------------+-----------+",
"| date | dayOfYear |",
"+------------+-----------+",
"| 2021-01-01 | 1 |",
"| 2021-01-02 | 2 |",
"| 2021-01-03 | 3 |",
"| 2021-01-04 | 4 |",
"| 2021-01-05 | 5 |",
"+------------+-----------+",
];
assert_batches_sorted_eq!(expected, &batches);
Ok(())
}
#[tokio::test]
async fn test_datafusion_date_column() -> Result<()> {
let ctx = SessionContext::new();
let table = deltalake::open_table("./tests/data/delta-0.8.0-date")
.await
.unwrap();
ctx.register_table("dates", Arc::new(table))?;
let batches = ctx
.sql("SELECT date from dates WHERE \"dayOfYear\" = 2")
.await?
.collect()
.await?;
assert_eq!(
batches[0].column(0).as_ref(),
Arc::new(Date32Array::from(vec![18629])).as_ref(),
);
Ok(())
}
#[tokio::test]
async fn test_datafusion_stats() -> Result<()> {
let table = deltalake::open_table("./tests/data/delta-0.8.0")
.await
.unwrap();
let statistics = table.datafusion_table_statistics();
assert_eq!(statistics.num_rows, Some(4),);
assert_eq!(statistics.total_byte_size, Some(440 + 440));
assert_eq!(
statistics
.column_statistics
.clone()
.unwrap()
.iter()
.map(|x| x.null_count)
.collect::<Vec<Option<usize>>>(),
vec![Some(0)],
);
let ctx = SessionContext::new();
ctx.register_table("test_table", Arc::new(table))?;
let batches = ctx
.sql("SELECT max(value), min(value) FROM test_table")
.await?
.collect()
.await?;
assert_eq!(batches.len(), 1);
let batch = &batches[0];
assert_eq!(
batch.column(0).as_ref(),
Arc::new(Int32Array::from(vec![4])).as_ref(),
);
assert_eq!(
batch.column(1).as_ref(),
Arc::new(Int32Array::from(vec![0])).as_ref(),
);
assert_eq!(
statistics
.column_statistics
.clone()
.unwrap()
.iter()
.map(|x| x.max_value.as_ref())
.collect::<Vec<Option<&ScalarValue>>>(),
vec![Some(&ScalarValue::from(4_i32))],
);
assert_eq!(
statistics
.column_statistics
.clone()
.unwrap()
.iter()
.map(|x| x.min_value.as_ref())
.collect::<Vec<Option<&ScalarValue>>>(),
vec![Some(&ScalarValue::from(0_i32))],
);
Ok(())
}
#[tokio::test]
async fn test_files_scanned() -> Result<()> {
let arrow_schema = Arc::new(ArrowSchema::new(vec![
ArrowField::new("id", ArrowDataType::Int32, true),
ArrowField::new("string", ArrowDataType::Utf8, true),
]));
let columns_1: Vec<ArrayRef> = vec![
Arc::new(Int32Array::from(vec![Some(1), Some(2)])),
Arc::new(StringArray::from(vec![Some("hello"), Some("world")])),
];
let columns_2: Vec<ArrayRef> = vec![
Arc::new(Int32Array::from(vec![Some(10), Some(20)])),
Arc::new(StringArray::from(vec![Some("hello"), Some("world")])),
];
let batches = vec![
RecordBatch::try_new(arrow_schema.clone(), columns_1)?,
RecordBatch::try_new(arrow_schema.clone(), columns_2)?,
];
let (_temp_dir, table) = prepare_table(batches, SaveMode::Append).await;
assert_eq!(table.version(), 2);
let ctx = SessionContext::new();
let plan = table.scan(&ctx.state(), None, &[], None).await?;
let plan = CoalescePartitionsExec::new(plan.clone());
let task_ctx = Arc::new(TaskContext::from(&ctx.state()));
let _ = collect(plan.execute(0, task_ctx)?).await?;
let mut metrics = ExecutionMetricsCollector::default();
visit_execution_plan(&plan, &mut metrics).unwrap();
assert!(metrics.num_scanned_files() == 2);
let filter = Expr::gt(
Expr::Column(Column::from_name("id")),
Expr::Literal(ScalarValue::Int32(Some(5))),
);
let plan = CoalescePartitionsExec::new(table.scan(&ctx.state(), None, &[filter], None).await?);
let task_ctx = Arc::new(TaskContext::from(&ctx.state()));
let _result = collect(plan.execute(0, task_ctx)?).await?;
let mut metrics = ExecutionMetricsCollector::default();
visit_execution_plan(&plan, &mut metrics).unwrap();
assert!(metrics.num_scanned_files() == 1);
Ok(())
}
#[tokio::test]
async fn test_datafusion_partitioned_types() -> Result<()> {
let ctx = SessionContext::new();
let table = deltalake::open_table("./tests/data/delta-2.2.0-partitioned-types")
.await
.unwrap();
ctx.register_table("demo", Arc::new(table))?;
let batches = ctx.sql("SELECT * FROM demo").await?.collect().await?;
let expected = vec![
"+----+----+----+",
"| c3 | c1 | c2 |",
"+----+----+----+",
"| 5 | 4 | c |",
"| 6 | 5 | b |",
"| 4 | 6 | a |",
"+----+----+----+",
];
assert_batches_sorted_eq!(&expected, &batches);
let expected_schema = ArrowSchema::new(vec![
ArrowField::new("c3", ArrowDataType::Int32, true),
ArrowField::new(
"c1",
ArrowDataType::Dictionary(
Box::new(ArrowDataType::UInt16),
Box::new(ArrowDataType::Int32),
),
false,
),
ArrowField::new(
"c2",
ArrowDataType::Dictionary(
Box::new(ArrowDataType::UInt16),
Box::new(ArrowDataType::Utf8),
),
false,
),
]);
assert_eq!(Arc::new(expected_schema), batches[0].schema());
Ok(())
}