JeonDaehong commented on code in PR #13771: URL: https://github.com/apache/iceberg/pull/13771#discussion_r2265066709
########## docs/docs/flink-table-maintenance.md: ########## @@ -0,0 +1,270 @@ +--- +title: "Flink Table Maintenance " +--- +<!-- + - 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. + --> + +# Flink Table Maintenance + +## Overview + +In **Apache Iceberg** deployments within **Flink streaming environments**, implementing automated table maintenance operations—including `snapshot expiration`, `small file compaction`, and `orphan file cleanup`—is critical for optimal performance and storage efficiency. + +Traditionally, these maintenance operations were exclusively accessible through **Iceberg Spark Actions**, necessitating the deployment and management of dedicated Spark clusters. This dependency on **Spark infrastructure** solely for table optimization introduces significant **architectural complexity** and **operational overhead**. + +The `TableMaintenance` API in **Apache Iceberg** empowers **Flink jobs** to execute maintenance tasks **natively**, either embedded within existing streaming pipelines or deployed as standalone Flink jobs. This eliminates dependencies on external systems, thereby **streamlining architecture**, **reducing operational costs**, and **enhancing automation capabilities**. + +## Quick Start + +The following example demonstrates the implementation of automated maintenance for an Iceberg table within a Flink environment. + +```java +StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); +TableLoader tableLoader = TableLoader.fromHadoopTable("path/to/table"); +TriggerLockFactory lockFactory = TriggerLockFactory.defaultLockFactory(); + +TableMaintenance.forTable(env, tableLoader, lockFactory) + .uidSuffix("my-maintenance-job") + .rateLimit(Duration.ofMinutes(10)) + .lockCheckDelay(Duration.ofSeconds(10)) + .add(ExpireSnapshots.builder() + .scheduleOnCommitCount(10) + .maxSnapshotAge(Duration.ofMinutes(10)) + .retainLast(5) + .deleteBatchSize(5) + .parallelism(8)) + .add(RewriteDataFiles.builder() + .scheduleOnDataFileCount(10) + .targetFileSizeBytes(128 * 1024 * 1024) + .partialProgressEnabled(true) + .partialProgressMaxCommits(10)) + .append(); + +env.execute("Table Maintenance Job"); +``` + +## Configuration Options + +### TableMaintenance Builder + +| Method | Description | Default | +|--------|-------------|---------| +| `uidSuffix(String)` | Unique identifier suffix for the job | Random UUID | +| `rateLimit(Duration)` | Minimum interval between task executions | 60 seconds | +| `lockCheckDelay(Duration)` | Delay for checking lock availability | 30 seconds | +| `parallelism(int)` | Default parallelism for maintenance tasks | System default | +| `maxReadBack(int)` | Max snapshots to check during initialization | 100 | + +### ExpireSnapshots Configuration + +| Method | Description | Default Value | Type | +|--------|-------------|---------------|------| +| `maxSnapshotAge(Duration)` | Maximum age of snapshots to retain | No limit | Duration | +| `retainLast(int)` | Minimum number of snapshots to retain | 1 | int | +| `deleteBatchSize(int)` | Number of files to delete in each batch | 1000 | int | +| `scheduleOnCommitCount(int)` | Trigger after N commits | No automatic scheduling | int | +| `scheduleOnDataFileCount(int)` | Trigger after N data files | No automatic scheduling | int | +| `scheduleOnDataFileSize(long)` | Trigger after total data file size (bytes) | No automatic scheduling | long | +| `scheduleOnIntervalSecond(long)` | Trigger after time interval (seconds) | No automatic scheduling | long | +| `parallelism(int)` | Parallelism for this specific task | Inherits from TableMaintenance | int | + + + +### RewriteDataFiles Configuration + +| Method | Description | Default Value | Type | +|--------|-------------|---------------|------| +| `targetFileSizeBytes(long)` | Target size for rewritten files | Table property or 512MB | long | +| `partialProgressEnabled(boolean)` | Enable partial progress commits | false | boolean | +| `partialProgressMaxCommits(int)` | Maximum commits for partial progress | 10 | int | +| `scheduleOnCommitCount(int)` | Trigger after N commits | 10 | int | +| `scheduleOnDataFileCount(int)` | Trigger after N data files | 1000 | int | +| `scheduleOnDataFileSize(long)` | Trigger after total data file size (bytes) | 100GB | long | +| `scheduleOnIntervalSecond(long)` | Trigger after time interval (seconds) | 600 (10 minutes) | long | +| `maxRewriteBytes(long)` | Maximum bytes to rewrite per execution | Long.MAX_VALUE | long | +| `parallelism(int)` | Parallelism for this specific task | Inherits from TableMaintenance | int | + +## Flink Configuration Options + +You can also configure maintenance behavior through Flink configuration: + +| Configuration Key | Description | Default Value | Type | +|-------------------|-------------|---------------|------| +| `iceberg.maintenance.rate-limit-seconds` | Rate limit in seconds | 60 | long | +| `iceberg.maintenance.lock-check-delay-seconds` | Lock check delay in seconds | 30 | long | +| `iceberg.maintenance.rewrite.max-bytes` | Maximum rewrite bytes | Long.MAX_VALUE | long | +| `iceberg.maintenance.rewrite.schedule.commit-count` | Schedule on commit count | 10 | int | +| `iceberg.maintenance.rewrite.schedule.data-file-count` | Schedule on data file count | 1000 | int | +| `iceberg.maintenance.rewrite.schedule.data-file-size` | Schedule on data file size | 100GB | long | +| `iceberg.maintenance.rewrite.schedule.interval-second` | Schedule interval in seconds | 600 | long | + + +## Complete Example + +```java +public class TableMaintenanceJob { + public static void main(String[] args) throws Exception { + StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); + env.enableCheckpointing(60000); // Enable checkpointing + + // Configure table loader + TableLoader tableLoader = TableLoader.fromCatalog( + CatalogLoader.hive("my_catalog", configuration), + TableIdentifier.of("database", "table") + ); + + // Set up maintenance with comprehensive configuration + TableMaintenance.forTable(env, tableLoader, TriggerLockFactory.defaultLockFactory()) + .uidSuffix("production-maintenance") + .rateLimit(Duration.ofMinutes(15)) + .lockCheckDelay(Duration.ofSeconds(30)) + .parallelism(4) + + // Daily snapshot cleanup + .add(ExpireSnapshots.builder() + .maxSnapshotAge(Duration.ofDays(7)) + .retainLast(10) + .deleteBatchSize(1000) + .scheduleOnCommitCount(50) + .parallelism(2)) + + // Continuous file optimization + .add(RewriteDataFiles.builder() + .targetFileSizeBytes(256 * 1024 * 1024) + .minFileSizeBytes(32 * 1024 * 1024) + .scheduleOnDataFileCount(20) + .partialProgressEnabled(true) + .partialProgressMaxCommits(5) + .maxRewriteBytes(2L * 1024 * 1024 * 1024) + .parallelism(6)) + + .append(); + + env.execute("Iceberg Table Maintenance"); + } +} +``` + +## Scheduling Options + +Maintenance tasks can be triggered based on various conditions: + +### Time-based Scheduling +```java +ExpireSnapshots.builder() + .scheduleOnIntervalSecond(3600) +``` + +### Commit-based Scheduling +```java +RewriteDataFiles.builder() + .scheduleOnCommitCount(50) +``` + +### Data Volume-based Scheduling +```java +RewriteDataFiles.builder() + .scheduleOnDataFileCount(500) + .scheduleOnDataFileSize(50L * 1024 * 1024 * 1024) +``` + +## IcebergSink with Post-Commit Integration + +Apache Iceberg Sink V2 for Flink allows automatic execution of maintenance tasks after data is committed to the table, using the addPostCommitTopology(...) method. + +```java +IcebergSink.forRowData(dataStream) + .table(table) + .tableLoader(tableLoader) + .setAll(properties) + .addPostCommitTopology( + TableMaintenance.forTable(env, tableLoader, TriggerLockFactory.defaultLockFactory()) + .rateLimit(Duration.ofMinutes(10)) + .add(ExpireSnapshots.builder().scheduleOnCommitCount(10)) + .add(RewriteDataFiles.builder().scheduleOnDataFileCount(50)) + ) Review Comment: I have reviewed it. 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