Support parquet_metadata for datafusion-cli

datafusion-cli/Cargo.toml

@@ -40,6 +40,7 @@ env_logger = "0.9"
 mimalloc = { version = "0.1", default-features = false }
 object_store = { version = "0.8.0", features = ["aws", "gcp"] }
 parking_lot = { version = "0.12" }
+parquet = { version = "49.0.0", default-features = false }
 regex = "1.8"
 rustyline = "11.0"
 tokio = { version = "1.24", features = ["macros", "rt", "rt-multi-thread", "sync", "parking_lot"] }

datafusion-cli/src/functions.rs

@@ -16,12 +16,26 @@
 // under the License.
 
 //! Functions that are query-able and searchable via the `\h` command
-use arrow::array::StringArray;
-use arrow::datatypes::{DataType, Field, Schema};
+use arrow::array::{Int64Array, StringArray};
+use arrow::datatypes::{DataType, Field, Schema, SchemaRef};
 use arrow::record_batch::RecordBatch;
 use arrow::util::pretty::pretty_format_batches;
+use async_trait::async_trait;
+use datafusion::common::DataFusionError;
+use datafusion::common::{plan_err, Column};
+use datafusion::datasource::function::TableFunctionImpl;
+use datafusion::datasource::TableProvider;
 use datafusion::error::Result;
+use datafusion::execution::context::SessionState;
+use datafusion::logical_expr::Expr;
+use datafusion::physical_plan::memory::MemoryExec;
+use datafusion::physical_plan::ExecutionPlan;
+use datafusion::scalar::ScalarValue;
+use parquet::file::reader::FileReader;
+use parquet::file::serialized_reader::SerializedFileReader;
+use parquet::file::statistics::Statistics;
 use std::fmt;
+use std::fs::File;
 use std::str::FromStr;
 use std::sync::Arc;
 
@@ -196,3 +210,208 @@ pub fn display_all_functions() -> Result<()> {
  println!("{}", pretty_format_batches(&[batch]).unwrap());
  Ok(())
 }
+
+/// PARQUET_META table function
+struct ParquetMetadataTable {
+ schema: SchemaRef,
+ batch: RecordBatch,
+}
+
+#[async_trait]
+impl TableProvider for ParquetMetadataTable {
+ fn as_any(&self) -> &dyn std::any::Any {
+ self
+ }
+
+ fn schema(&self) -> arrow::datatypes::SchemaRef {
+ self.schema.clone()
+ }
+
+ fn table_type(&self) -> datafusion::logical_expr::TableType {
+ datafusion::logical_expr::TableType::Base
+ }
+
+ async fn scan(
+ &self,
+ _state: &SessionState,
+ projection: Option<&Vec<usize>>,
+ _filters: &[Expr],
+ _limit: Option<usize>,
+ ) -> Result<Arc<dyn ExecutionPlan>> {
+ Ok(Arc::new(MemoryExec::try_new(
+ &[vec![self.batch.clone()]],
+ TableProvider::schema(self),
+ projection.cloned(),
+ )?))
+ }
+}
+
+pub struct ParquetMetadataFunc {}
+
+impl TableFunctionImpl for ParquetMetadataFunc {
+ fn call(&self, exprs: &[Expr]) -> Result<Arc<dyn TableProvider>> {
+ let filename = match exprs.get(0) {
+ Some(Expr::Literal(ScalarValue::Utf8(Some(s)))) => s, // single quote: parquet_metadata('x.parquet')
+ Some(Expr::Column(Column { name, .. })) => name, // double quote: parquet_metadata("x.parquet")
+ _ => {
+ return plan_err!(
+ "parquet_metadata requires string argument as its input"
+ );
+ }
+ };
+
+ let file = File::open(filename.clone())?;
+ let reader = SerializedFileReader::new(file)?;
+ let metadata = reader.metadata();
+
+ let schema = Arc::new(Schema::new(vec![
+ Field::new("filename", DataType::Utf8, true),
+ Field::new("row_group_id", DataType::Int64, true),
+ Field::new("row_group_num_rows", DataType::Int64, true),
+ Field::new("row_group_num_columns", DataType::Int64, true),
+ Field::new("row_group_bytes", DataType::Int64, true),
+ Field::new("column_id", DataType::Int64, true),
+ Field::new("file_offset", DataType::Int64, true),
+ Field::new("num_values", DataType::Int64, true),
+ Field::new("path_in_schema", DataType::Utf8, true),
+ Field::new("type", DataType::Utf8, true),
+ Field::new("stats_min", DataType::Utf8, true),
+ Field::new("stats_max", DataType::Utf8, true),
+ Field::new("stats_null_count", DataType::Int64, true),
+ Field::new("stats_distinct_count", DataType::Int64, true),
+ Field::new("stats_min_value", DataType::Utf8, true),
+ Field::new("stats_max_value", DataType::Utf8, true),
+ Field::new("compression", DataType::Utf8, true),
+ Field::new("encodings", DataType::Utf8, true),
+ Field::new("index_page_offset", DataType::Int64, true),
+ Field::new("dictionary_page_offset", DataType::Int64, true),
+ Field::new("data_page_offset", DataType::Int64, true),
+ Field::new("total_compressed_size", DataType::Int64, true),
+ Field::new("total_uncompressed_size", DataType::Int64, true),
+ ]));
+
+ // construct recordbatch from metadata
+ let mut filename_arr = vec![];
+ let mut row_group_id_arr = vec![];
+ let mut row_group_num_rows_arr = vec![];
+ let mut row_group_num_columns_arr = vec![];
+ let mut row_group_bytes_arr = vec![];
+ let mut column_id_arr = vec![];
+ let mut file_offset_arr = vec![];
+ let mut num_values_arr = vec![];
+ let mut path_in_schema_arr = vec![];
+ let mut type_arr = vec![];
+ let mut stats_min_arr = vec![];
+ let mut stats_max_arr = vec![];
+ let mut stats_null_count_arr = vec![];
+ let mut stats_distinct_count_arr = vec![];
+ let mut stats_min_value_arr = vec![];
+ let mut stats_max_value_arr = vec![];
+ let mut compression_arr = vec![];
+ let mut encodings_arr = vec![];
+ let mut index_page_offset_arr = vec![];
+ let mut dictionary_page_offset_arr = vec![];
+ let mut data_page_offset_arr = vec![];
+ let mut total_compressed_size_arr = vec![];
+ let mut total_uncompressed_size_arr = vec![];
+ for (rg_idx, row_group) in metadata.row_groups().iter().enumerate() {
+ for (col_idx, column) in row_group.columns().iter().enumerate() {
+ filename_arr.push(filename.clone());
+ row_group_id_arr.push(rg_idx as i64);
+ row_group_num_rows_arr.push(row_group.num_rows());
+ row_group_num_columns_arr.push(row_group.num_columns() as i64);
+ row_group_bytes_arr.push(row_group.total_byte_size());
+ column_id_arr.push(col_idx as i64);
+ file_offset_arr.push(column.file_offset());
+ num_values_arr.push(column.num_values());
+ path_in_schema_arr.push(column.column_path().to_string());
+ type_arr.push(column.column_type().to_string());
+ if let Some(s) = column.statistics() {
+ let (min_val, max_val) = if s.has_min_max_set() {
+ let (min_val, max_val) = match s {
+ Statistics::Boolean(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::Int32(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::Int64(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::Int96(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::Float(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::Double(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::ByteArray(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ Statistics::FixedLenByteArray(val) => {
+ (val.min().to_string(), val.max().to_string())
+ }
+ };
+ (Some(min_val), Some(max_val))
+ } else {
+ (None, None)
+ };
+ stats_min_arr.push(min_val.clone());
+ stats_max_arr.push(max_val.clone());
+ stats_null_count_arr.push(Some(s.null_count() as i64));
+ stats_distinct_count_arr.push(s.distinct_count().map(|c| c as i64));
+ stats_min_value_arr.push(min_val);
+ stats_max_value_arr.push(max_val);
+ } else {
+ stats_min_arr.push(None);
+ stats_max_arr.push(None);
+ stats_null_count_arr.push(None);
+ stats_distinct_count_arr.push(None);
+ stats_min_value_arr.push(None);
+ stats_max_value_arr.push(None);
+ };
+ compression_arr.push(format!("{:?}", column.compression()));
+ encodings_arr.push(format!("{:?}", column.encodings()));
+ index_page_offset_arr.push(column.index_page_offset());
+ dictionary_page_offset_arr.push(column.dictionary_page_offset());
+ data_page_offset_arr.push(column.data_page_offset());
+ total_compressed_size_arr.push(column.compressed_size());
+ total_uncompressed_size_arr.push(column.uncompressed_size());
+ }
+ }
+
+ let rb = RecordBatch::try_new(
+ schema.clone(),
+ vec![
+ Arc::new(StringArray::from(filename_arr)),
+ Arc::new(Int64Array::from(row_group_id_arr)),
+ Arc::new(Int64Array::from(row_group_num_rows_arr)),
+ Arc::new(Int64Array::from(row_group_num_columns_arr)),
+ Arc::new(Int64Array::from(row_group_bytes_arr)),
+ Arc::new(Int64Array::from(column_id_arr)),
+ Arc::new(Int64Array::from(file_offset_arr)),
+ Arc::new(Int64Array::from(num_values_arr)),
+ Arc::new(StringArray::from(path_in_schema_arr)),
+ Arc::new(StringArray::from(type_arr)),
+ Arc::new(StringArray::from(stats_min_arr)),
+ Arc::new(StringArray::from(stats_max_arr)),
+ Arc::new(Int64Array::from(stats_null_count_arr)),
+ Arc::new(Int64Array::from(stats_distinct_count_arr)),
+ Arc::new(StringArray::from(stats_min_value_arr)),
+ Arc::new(StringArray::from(stats_max_value_arr)),
+ Arc::new(StringArray::from(compression_arr)),
+ Arc::new(StringArray::from(encodings_arr)),
+ Arc::new(Int64Array::from(index_page_offset_arr)),
+ Arc::new(Int64Array::from(dictionary_page_offset_arr)),
+ Arc::new(Int64Array::from(data_page_offset_arr)),
+ Arc::new(Int64Array::from(total_compressed_size_arr)),
+ Arc::new(Int64Array::from(total_uncompressed_size_arr)),
+ ],
+ )?;
+
+ let parquet_metadata = ParquetMetadataTable { schema, batch: rb };
+ Ok(Arc::new(parquet_metadata))
+ }
+}

datafusion-cli/src/main.rs

@@ -22,6 +22,7 @@ use datafusion::execution::memory_pool::{FairSpillPool, GreedyMemoryPool};
 use datafusion::execution::runtime_env::{RuntimeConfig, RuntimeEnv};
 use datafusion::prelude::SessionContext;
 use datafusion_cli::catalog::DynamicFileCatalog;
+use datafusion_cli::functions::ParquetMetadataFunc;
 use datafusion_cli::{
  exec,
  print_format::PrintFormat,
@@ -185,6 +186,8 @@ pub async fn main() -> Result<()> {
  ctx.state().catalog_list(),
  ctx.state_weak_ref(),
  )));
+ // register `parquet_metadata` table function to get metadata from parquet files
+ ctx.register_udtf("parquet_metadata", Arc::new(ParquetMetadataFunc {}));
 
  let mut print_options = PrintOptions {
  format: args.format,
@@ -328,6 +331,8 @@ fn extract_memory_pool_size(size: &str) -> Result<usize, String> {
 
 #[cfg(test)]
 mod tests {
+ use datafusion::assert_batches_eq;
+
  use super::*;
 
  fn assert_conversion(input: &str, expected: Result<usize, String>) {
@@ -385,4 +390,34 @@ mod tests {
 
  Ok(())
  }
+
+ #[tokio::test]
+ async fn test_parquet_metadata_works() -> Result<(), DataFusionError> {
+ let ctx = SessionContext::new();
+ ctx.register_udtf("parquet_metadata", Arc::new(ParquetMetadataFunc {}));
+
+ // input with single quote
+ let sql =
+ "SELECT * FROM parquet_metadata('../datafusion/core/tests/data/fixed_size_list_array.parquet')";
+ let df = ctx.sql(sql).await?;
+ let rbs = df.collect().await?;
+
+ let excepted = [
+ "+-------------------------------------------------------------+--------------+--------------------+-----------------------+-----------------+-----------+-------------+------------+----------------+-------+-----------+-----------+------------------+----------------------+-----------------+-----------------+-------------+------------------------------+-------------------+------------------------+------------------+-----------------------+-------------------------+",
+ "| filename | row_group_id | row_group_num_rows | row_group_num_columns | row_group_bytes | column_id | file_offset | num_values | path_in_schema | type | stats_min | stats_max | stats_null_count | stats_distinct_count | stats_min_value | stats_max_value | compression | encodings | index_page_offset | dictionary_page_offset | data_page_offset | total_compressed_size | total_uncompressed_size |",
+ "+-------------------------------------------------------------+--------------+--------------------+-----------------------+-----------------+-----------+-------------+------------+----------------+-------+-----------+-----------+------------------+----------------------+-----------------+-----------------+-------------+------------------------------+-------------------+------------------------+------------------+-----------------------+-------------------------+",
+ "| ../datafusion/core/tests/data/fixed_size_list_array.parquet | 0 | 2 | 1 | 123 | 0 | 125 | 4 | \"f0.list.item\" | INT64 | 1 | 4 | 0 | | 1 | 4 | SNAPPY | [RLE_DICTIONARY, PLAIN, RLE] | | 4 | 46 | 121 | 123 |",
+ "+-------------------------------------------------------------+--------------+--------------------+-----------------------+-----------------+-----------+-------------+------------+----------------+-------+-----------+-----------+------------------+----------------------+-----------------+-----------------+-------------+------------------------------+-------------------+------------------------+------------------+-----------------------+-------------------------+",
+ ];
+ assert_batches_eq!(excepted, &rbs);
+
+ // input with double quote
+ let sql =
+ "SELECT * FROM parquet_metadata(\"../datafusion/core/tests/data/fixed_size_list_array.parquet\")";
+ let df = ctx.sql(sql).await?;
+ let rbs = df.collect().await?;
+ assert_batches_eq!(excepted, &rbs);
+
+ Ok(())
+ }
 }