zhuqi-lucas commented on code in PR #16395:
URL: https://github.com/apache/datafusion/pull/16395#discussion_r2148132009


##########
datafusion-examples/examples/embedding_parquet_indexes.rs:
##########
@@ -0,0 +1,243 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! Example: embedding a "distinct values" index in a Parquet file's metadata
+//!
+//! 1. Read existing Parquet files
+//! 2. Compute distinct values for a target column using DataFusion
+//! 3. Serialize the distinct index to bytes and write to the new Parquet file
+//!    with these encoded bytes appended as a custom metadata entry
+//! 4. Read each new parquet file, extract and deserialize the index from 
footer
+//! 5. Use the distinct index to prune files when querying
+
+use arrow::array::{ArrayRef, StringArray};
+use arrow::record_batch::RecordBatch;
+use arrow_schema::{DataType, Field, Schema, SchemaRef};
+use async_trait::async_trait;
+use base64::engine::general_purpose;
+use base64::Engine;
+use datafusion::catalog::{Session, TableProvider};
+use datafusion::common::{HashMap, HashSet, Result};
+use datafusion::datasource::listing::PartitionedFile;
+use datafusion::datasource::memory::DataSourceExec;
+use datafusion::datasource::physical_plan::{FileScanConfigBuilder, 
ParquetSource};
+use datafusion::datasource::TableType;
+use datafusion::execution::object_store::ObjectStoreUrl;
+use datafusion::logical_expr::{Operator, TableProviderFilterPushDown};
+use datafusion::parquet::arrow::ArrowWriter;
+use datafusion::parquet::file::metadata::KeyValue;
+use datafusion::parquet::file::properties::WriterProperties;
+use datafusion::parquet::file::reader::{FileReader, SerializedFileReader};
+use datafusion::physical_plan::ExecutionPlan;
+use datafusion::prelude::*;
+use datafusion::scalar::ScalarValue;
+use std::fs::{create_dir_all, read_dir, File};
+use std::path::{Path, PathBuf};
+use std::sync::Arc;
+use tempfile::TempDir;
+
+/// Example creating parquet file that
+/// contains specialized indexes that
+/// are ignored by other readers
+///
+/// ```text
+///         ┌──────────────────────┐
+///         │┌───────────────────┐ │
+///         ││     DataPage      │ │      Standard Parquet
+///         │└───────────────────┘ │      Data / pages
+///         │┌───────────────────┐ │
+///         ││     DataPage      │ │
+///         │└───────────────────┘ │
+///         │        ...           │
+///         │                      │
+///         │┌───────────────────┐ │
+///         ││     DataPage      │ │
+///         │└───────────────────┘ │
+///         │┏━━━━━━━━━━━━━━━━━━━┓ │
+///         │┃                   ┃ │        key/value metadata
+///         │┃   Special Index   ┃◀┼────    that points at the
+///         │┃                   ┃ │     │  special index
+///         │┗━━━━━━━━━━━━━━━━━━━┛ │
+///         │╔═══════════════════╗ │     │
+///         │║                   ║ │
+///         │║  Parquet Footer   ║ │     │  Footer includes
+///         │║                   ║ ┼──────  thrift-encoded
+///         │║                   ║ │        ParquetMetadata
+///         │╚═══════════════════╝ │
+///         └──────────────────────┘
+///
+///               Parquet File
+/// ```
+/// DistinctIndexTable is a custom TableProvider that reads Parquet files
+#[derive(Debug)]
+struct DistinctIndexTable {
+    schema: SchemaRef,
+    index: HashMap<String, HashSet<String>>,
+    dir: PathBuf,
+}
+
+impl DistinctIndexTable {
+    /// Scan a directory, read each file's footer metadata into a map
+    fn try_new(dir: impl Into<PathBuf>, schema: SchemaRef) -> Result<Self> {
+        let dir = dir.into();
+        let mut index = HashMap::new();
+        for entry in read_dir(&dir)? {
+            let p = entry?.path();
+            if p.extension().and_then(|s| s.to_str()) != Some("parquet") {
+                continue;
+            }
+            let name = p.file_name().unwrap().to_string_lossy().into_owned();
+            let reader = SerializedFileReader::new(File::open(&p)?)?;
+            if let Some(kv) = 
reader.metadata().file_metadata().key_value_metadata() {
+                if let Some(e) = kv.iter().find(|kv| kv.key == 
"distinct_index_data") {
+                    let raw = general_purpose::STANDARD_NO_PAD
+                        .decode(e.value.as_deref().unwrap())
+                        .unwrap();
+                    let s = String::from_utf8(raw).unwrap();
+                    let set = s.lines().map(|l| l.to_string()).collect();
+                    println!("Inserting  File: {name}, Distinct Values: 
{set:?}");
+                    index.insert(name, set);
+                }
+            }
+        }
+        Ok(Self { schema, index, dir })
+    }
+}
+
+// Write a Parquet file and embed its distinct "category" values in footer 
metadata
+fn write_file_with_index(path: &Path, values: &[&str]) -> Result<()> {
+    let field = Field::new("category", DataType::Utf8, false);
+    let schema = Arc::new(Schema::new(vec![field.clone()]));
+    let arr: ArrayRef = Arc::new(StringArray::from(values.to_vec()));
+    let batch = RecordBatch::try_new(schema.clone(), vec![arr])?;
+
+    // Compute distinct values, serialize & Base64‑encode
+    let distinct: HashSet<_> = values.iter().copied().collect();
+    let serialized = distinct.iter().cloned().collect::<Vec<_>>().join("\n");
+    let b64 = general_purpose::STANDARD_NO_PAD.encode(serialized.as_bytes());

Review Comment:
   The code is here:
   
   ```rust
   diff --git a/datafusion-examples/examples/embedding_parquet_indexes.rs 
b/datafusion-examples/examples/embedding_parquet_indexes.rs
   new file mode 100644
   index 000000000..9462ed092
   --- /dev/null
   +++ b/datafusion-examples/examples/embedding_parquet_indexes.rs
   @@ -0,0 +1,360 @@
   +// Licensed to the Apache Software Foundation (ASF) under one
   +// or more contributor license agreements.  See the NOTICE file
   +// distributed with this work for additional information
   +// regarding copyright ownership.  The ASF licenses this file
   +// to you under the Apache License, Version 2.0 (the
   +// "License"); you may not use this file except in compliance
   +// with the License.  You may obtain a copy of the License at
   +//
   +//   http://www.apache.org/licenses/LICENSE-2.0
   +//
   +// Unless required by applicable law or agreed to in writing,
   +// software distributed under the License is distributed on an
   +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
   +// KIND, either express or implied.  See the License for the
   +// specific language governing permissions and limitations
   +// under the License.
   +
   +//! Example: embedding a "distinct values" index in a Parquet file's 
metadata
   +//!
   +//! 1. Read existing Parquet files
   +//! 2. Compute distinct values for a target column using DataFusion
   +//! 3. Serialize the distinct index to bytes and write to the new Parquet 
file
   +//!    with these encoded bytes appended as a custom metadata entry
   +//! 4. Read each new parquet file, extract and deserialize the index from 
footer
   +//! 5. Use the distinct index to prune files when querying
   +
   +use arrow::array::{ArrayRef, StringArray};
   +use arrow::record_batch::RecordBatch;
   +use arrow_schema::{DataType, Field, Schema, SchemaRef};
   +use async_trait::async_trait;
   +use datafusion::catalog::{Session, TableProvider};
   +use datafusion::common::{HashMap, HashSet, Result};
   +use datafusion::datasource::listing::PartitionedFile;
   +use datafusion::datasource::memory::DataSourceExec;
   +use datafusion::datasource::physical_plan::{FileScanConfigBuilder, 
ParquetSource};
   +use datafusion::datasource::TableType;
   +use datafusion::execution::object_store::ObjectStoreUrl;
   +use datafusion::logical_expr::{Operator, TableProviderFilterPushDown};
   +use datafusion::parquet::arrow::ArrowSchemaConverter;
   +use datafusion::parquet::data_type::{ByteArray, ByteArrayType};
   +use datafusion::parquet::errors::ParquetError;
   +use datafusion::parquet::file::metadata::KeyValue;
   +use datafusion::parquet::file::properties::WriterProperties;
   +use datafusion::parquet::file::reader::{FileReader, SerializedFileReader};
   +use datafusion::parquet::file::writer::SerializedFileWriter;
   +use datafusion::physical_plan::ExecutionPlan;
   +use datafusion::prelude::*;
   +use datafusion::scalar::ScalarValue;
   +use futures::AsyncWriteExt;
   +use std::fs::{create_dir_all, read_dir, File};
   +use std::io::{Read, Seek, SeekFrom, Write};
   +use std::path::{Path, PathBuf};
   +use std::sync::Arc;
   +use tempfile::TempDir;
   +
   +/// We should disable page index support in the Parquet reader
   +/// when we ennable this feature, since we are using a custom index.
   +///
   +/// Example creating parquet file that
   +/// contains specialized indexes that
   +/// are ignored by other readers
   +///
   +/// ```text
   +///         ┌──────────────────────┐
   +///         │┌───────────────────┐ │
   +///         ││     DataPage      │ │      Standard Parquet
   +///         │└───────────────────┘ │      Data / pages
   +///         │┌───────────────────┐ │
   +///         ││     DataPage      │ │
   +///         │└───────────────────┘ │
   +///         │        ...           │
   +///         │                      │
   +///         │┌───────────────────┐ │
   +///         ││     DataPage      │ │
   +///         │└───────────────────┘ │
   +///         │┏━━━━━━━━━━━━━━━━━━━┓ │
   +///         │┃                   ┃ │        key/value metadata
   +///         │┃   Special Index   ┃◀┼────    that points at the
   +///         │┃                   ┃ │     │  special index
   +///         │┗━━━━━━━━━━━━━━━━━━━┛ │
   +///         │╔═══════════════════╗ │     │
   +///         │║                   ║ │
   +///         │║  Parquet Footer   ║ │     │  Footer includes
   +///         │║                   ║ ┼──────  thrift-encoded
   +///         │║                   ║ │        ParquetMetadata
   +///         │╚═══════════════════╝ │
   +///         └──────────────────────┘
   +///
   +///               Parquet File
   +/// ```
   +/// DistinctIndexTable is a custom TableProvider that reads Parquet files
   +#[derive(Debug)]
   +struct DistinctIndexTable {
   +    schema: SchemaRef,
   +    index: HashMap<String, HashSet<String>>,
   +    dir: PathBuf,
   +}
   +
   +impl DistinctIndexTable {
   +    /// Scan a directory, read each file's footer metadata into a map
   +    fn try_new(dir: impl Into<PathBuf>, schema: SchemaRef) -> Result<Self> {
   +        let dir = dir.into();
   +        let mut index = HashMap::new();
   +
   +        for entry in read_dir(&dir)? {
   +            let path = entry?.path();
   +            if path.extension().and_then(|s| s.to_str()) != Some("parquet") 
{
   +                continue;
   +            }
   +            let file_name = 
path.file_name().unwrap().to_string_lossy().to_string();
   +
   +            // 直接用工具函数读取该文件的 distinct index
   +            let distinct_set = read_distinct_index(&path)?;
   +
   +            println!("Read distinct index for {}: {:?}", file_name, 
distinct_set);
   +            index.insert(file_name, distinct_set);
   +        }
   +
   +        Ok(Self { schema, index, dir })
   +    }
   +}
   +
   +pub struct IndexedParquetWriter<W: Write + Seek> {
   +    writer: SerializedFileWriter<W>,
   +}
   +
   +impl<W: Write + Seek + Send> IndexedParquetWriter<W> {
   +    pub fn try_new(
   +        sink: W,
   +        schema: Arc<Schema>,
   +        props: WriterProperties,
   +    ) -> Result<Self> {
   +        let schema_desc = 
ArrowSchemaConverter::new().convert(schema.as_ref())?;
   +        let props_ptr = Arc::new(props);
   +        let writer =
   +            SerializedFileWriter::new(sink, schema_desc.root_schema_ptr(), 
props_ptr)?;
   +        Ok(Self { writer })
   +    }
   +}
   +
   +const INDEX_MAGIC: &[u8] = b"IDX1";
   +
   +fn write_file_with_index(path: &Path, values: &[&str]) -> Result<()> {
   +    let field = Field::new("category", DataType::Utf8, false);
   +    let schema = Arc::new(Schema::new(vec![field.clone()]));
   +    let arr: ArrayRef = Arc::new(StringArray::from(values.to_vec()));
   +    let batch = RecordBatch::try_new(schema.clone(), vec![arr])?;
   +
   +    let distinct: HashSet<_> = values.iter().copied().collect();
   +    let serialized = distinct.into_iter().collect::<Vec<_>>().join("\n");
   +    let index_bytes = serialized.into_bytes();
   +
   +    let props = WriterProperties::builder().build();
   +    let file = File::create(path)?;
   +
   +    let mut writer = IndexedParquetWriter::try_new(file, schema.clone(), 
props)?;
   +
   +    {
   +        let mut rg_writer = writer.writer.next_row_group()?;
   +        let mut ser_col_writer = rg_writer
   +            .next_column()?
   +            .ok_or_else(|| ParquetError::General("No column 
writer".into()))?;
   +
   +        let col_writer = ser_col_writer.typed::<ByteArrayType>();
   +        let values_bytes: Vec<ByteArray> = batch
   +            .column(0)
   +            .as_any()
   +            .downcast_ref::<StringArray>()
   +            .unwrap()
   +            .iter()
   +            .map(|opt| ByteArray::from(opt.unwrap()))
   +            .collect();
   +
   +        println!("Writing values: {:?}", values_bytes);
   +        col_writer.write_batch(&values_bytes, None, None)?;
   +        ser_col_writer.close()?;
   +        rg_writer.close()?;
   +    }
   +
   +    let offset = writer.writer.inner().seek(SeekFrom::Current(0))?;
   +
   +    let index_len = index_bytes.len() as u64;
   +    writer.writer.inner().write_all(b"IDX1")?; // 4字节魔术字
   +    writer.writer.inner().write_all(&index_len.to_le_bytes())?; // 8字节长度
   +
   +    writer.writer.inner().write_all(&index_bytes)?;
   +
   +    writer.writer.append_key_value_metadata(KeyValue::new(
   +        "distinct_index_offset".to_string(),
   +        offset.to_string(),
   +    ));
   +    writer.writer.append_key_value_metadata(KeyValue::new(
   +        "distinct_index_length".to_string(),
   +        index_bytes.len().to_string(),
   +    ));
   +
   +    writer.writer.close()?;
   +
   +    println!("Finished writing file to {}", path.display());
   +    Ok(())
   +}
   +
   +fn read_distinct_index(path: &Path) -> Result<HashSet<String>, 
ParquetError> {
   +    let mut file = File::open(path)?;
   +
   +    let file_size = file.metadata()?.len();
   +    println!(
   +        "Reading index from {} (size: {})",
   +        path.display(),
   +        file_size
   +    );
   +
   +    let reader = SerializedFileReader::new(file.try_clone()?)?;
   +    let meta = reader.metadata().file_metadata();
   +
   +    let offset = meta
   +        .key_value_metadata()
   +        .and_then(|kvs| kvs.iter().find(|kv| kv.key == 
"distinct_index_offset"))
   +        .and_then(|kv| kv.value.as_ref())
   +        .ok_or_else(|| ParquetError::General("Missing index 
offset".into()))?
   +        .parse::<u64>()
   +        .map_err(|e| ParquetError::General(e.to_string()))?;
   +
   +    let length = meta
   +        .key_value_metadata()
   +        .and_then(|kvs| kvs.iter().find(|kv| kv.key == 
"distinct_index_length"))
   +        .and_then(|kv| kv.value.as_ref())
   +        .ok_or_else(|| ParquetError::General("Missing index 
length".into()))?
   +        .parse::<usize>()
   +        .map_err(|e| ParquetError::General(e.to_string()))?;
   +
   +    println!("Reading index at offset: {}, length: {}", offset, length);
   +
   +    file.seek(SeekFrom::Start(offset))?;
   +
   +    let mut magic_buf = [0u8; 4];
   +    file.read_exact(&mut magic_buf)?;
   +    if &magic_buf != INDEX_MAGIC {
   +        return Err(ParquetError::General("Invalid index magic".into()));
   +    }
   +
   +    let mut len_buf = [0u8; 8];
   +    file.read_exact(&mut len_buf)?;
   +    let stored_len = u64::from_le_bytes(len_buf) as usize;
   +
   +    if stored_len != length {
   +        return Err(ParquetError::General("Index length mismatch".into()));
   +    }
   +
   +    let mut index_buf = vec![0u8; length];
   +    file.read_exact(&mut index_buf)?;
   +
   +    let s =
   +        String::from_utf8(index_buf).map_err(|e| 
ParquetError::General(e.to_string()))?;
   +
   +    Ok(s.lines().map(|s| s.to_string()).collect())
   +}
   +
   +/// Implement TableProvider for DistinctIndexTable, using the distinct 
index to prune files
   +#[async_trait]
   +impl TableProvider for DistinctIndexTable {
   +    fn as_any(&self) -> &dyn std::any::Any {
   +        self
   +    }
   +    fn schema(&self) -> SchemaRef {
   +        self.schema.clone()
   +    }
   +    fn table_type(&self) -> TableType {
   +        TableType::Base
   +    }
   +
   +    /// Prune files before reading: only keep files whose distinct set 
contains the filter value
   +    async fn scan(
   +        &self,
   +        _ctx: &dyn Session,
   +        _proj: Option<&Vec<usize>>,
   +        filters: &[Expr],
   +        _limit: Option<usize>,
   +    ) -> Result<Arc<dyn ExecutionPlan>> {
   +        // Look for a single `category = 'X'` filter
   +        let mut target: Option<String> = None;
   +
   +        if filters.len() == 1 {
   +            if let Expr::BinaryExpr(expr) = &filters[0] {
   +                if expr.op == Operator::Eq {
   +                    if let (
   +                        Expr::Column(c),
   +                        Expr::Literal(ScalarValue::Utf8(Some(v)), _),
   +                    ) = (&*expr.left, &*expr.right)
   +                    {
   +                        if c.name == "category" {
   +                            println!("Filtering for category: {v}");
   +                            target = Some(v.clone());
   +                        }
   +                    }
   +                }
   +            }
   +        }
   +        // Determine which files to scan
   +        let keep: Vec<String> = self
   +            .index
   +            .iter()
   +            .filter(|(_f, set)| target.as_ref().is_none_or(|v| 
set.contains(v)))
   +            .map(|(f, _)| f.clone())
   +            .collect();
   +
   +        println!("Pruned files: {:?}", keep.clone());
   +
   +        // Build ParquetSource for kept files
   +        let url = ObjectStoreUrl::parse("file://")?;
   +        let source = Arc::new(ParquetSource::default());
   +        let mut builder = FileScanConfigBuilder::new(url, 
self.schema.clone(), source);
   +        for file in keep {
   +            let path = self.dir.join(&file);
   +            let len = std::fs::metadata(&path)?.len();
   +            builder = builder.with_file(PartitionedFile::new(
   +                path.to_str().unwrap().to_string(),
   +                len,
   +            ));
   +        }
   +        Ok(DataSourceExec::from_data_source(builder.build()))
   +    }
   +
   +    fn supports_filters_pushdown(
   +        &self,
   +        fs: &[&Expr],
   +    ) -> Result<Vec<TableProviderFilterPushDown>> {
   +        // Mark as inexact since pruning is file‑granular
   +        Ok(vec![TableProviderFilterPushDown::Inexact; fs.len()])
   +    }
   +}
   +
   +#[tokio::main]
   +async fn main() -> Result<()> {
   +    // 1. Create temp dir and write 3 Parquet files with different category 
sets
   +    let tmp = TempDir::new()?;
   +    let dir = tmp.path();
   +    create_dir_all(dir)?;
   +    write_file_with_index(&dir.join("a.parquet"), &["foo", "bar", "foo"])?;
   +    write_file_with_index(&dir.join("b.parquet"), &["baz", "qux"])?;
   +    write_file_with_index(&dir.join("c.parquet"), &["foo", "quux", 
"quux"])?;
   +
   +    // 2. Register our custom TableProvider
   +    let field = Field::new("category", DataType::Utf8, false);
   +    let schema_ref = Arc::new(Schema::new(vec![field]));
   +    let provider = Arc::new(DistinctIndexTable::try_new(dir, 
schema_ref.clone())?);
   +    let ctx = SessionContext::new();
   +
   +    ctx.register_table("t", provider)?;
   +
   +    // 3. Run a query: only files containing 'foo' get scanned
   +    let df = ctx.sql("SELECT * FROM t").await?;
   +    df.show().await?;
   +
   +    // 3. Run a query: only files containing 'foo' get scanned
   +    let df = ctx.sql("SELECT * FROM t WHERE category = 'foo'").await?;
   +    df.show().await?;
   +
   +    Ok(())
   +}
   
   ```



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