Guosmilesmile commented on code in PR #13360: URL: https://github.com/apache/iceberg/pull/13360#discussion_r2159805226
########## docs/docs/flink-table-maintenance.md: ########## @@ -0,0 +1,268 @@ +--- +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 +When using **Apache Iceberg tables** in a **Flink streaming environment**, it's important to automate table maintenance operations such as `snapshot expiration`, `small file compaction`, and `orphan file cleanup`. + +Previously, these maintenance tasks were only available through **Iceberg Spark Actions**, requiring a separate Spark cluster. However, maintaining **Spark infrastructure** just for table optimization adds **complexity** and **operational overhead**. + +The `TableMaintenance` API in **Apache Iceberg** enables **Flink jobs** to execute these maintenance tasks **natively** within the same streaming job or as an independent Flink job, avoiding the need for external systems. This approach simplifies **architecture**, reduces **costs**, and improves **automation**. + +## Quick Start +Here's a simple example that sets up automated maintenance for an Iceberg table. + +```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( Review Comment: Users neither need to nor can call the addPostCommitTopology method. Compression in the sink is enabled through configuration. ########## docs/docs/flink-table-maintenance.md: ########## @@ -0,0 +1,268 @@ +--- +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 +When using **Apache Iceberg tables** in a **Flink streaming environment**, it's important to automate table maintenance operations such as `snapshot expiration`, `small file compaction`, and `orphan file cleanup`. + +Previously, these maintenance tasks were only available through **Iceberg Spark Actions**, requiring a separate Spark cluster. However, maintaining **Spark infrastructure** just for table optimization adds **complexity** and **operational overhead**. + +The `TableMaintenance` API in **Apache Iceberg** enables **Flink jobs** to execute these maintenance tasks **natively** within the same streaming job or as an independent Flink job, avoiding the need for external systems. This approach simplifies **architecture**, reduces **costs**, and improves **automation**. + +## Quick Start +Here's a simple example that sets up automated maintenance for an Iceberg table. + +```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 | Review Comment: Are there some configurations that we haven't listed, like `minInputFiles`, `rewriteAll`, `maxFileGroupSizeBytes`, and so on? ########## docs/docs/flink-table-maintenance.md: ########## @@ -0,0 +1,268 @@ +--- +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 +When using **Apache Iceberg tables** in a **Flink streaming environment**, it's important to automate table maintenance operations such as `snapshot expiration`, `small file compaction`, and `orphan file cleanup`. + +Previously, these maintenance tasks were only available through **Iceberg Spark Actions**, requiring a separate Spark cluster. However, maintaining **Spark infrastructure** just for table optimization adds **complexity** and **operational overhead**. + +The `TableMaintenance` API in **Apache Iceberg** enables **Flink jobs** to execute these maintenance tasks **natively** within the same streaming job or as an independent Flink job, avoiding the need for external systems. This approach simplifies **architecture**, reduces **costs**, and improves **automation**. + +## Quick Start +Here's a simple example that sets up automated maintenance for an Iceberg table. + +```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 | Review Comment: Regarding the configuration items for this part, I'm a bit unfamiliar. Are these all the configuration items? And where are they used? ########## docs/docs/flink-table-maintenance.md: ########## @@ -0,0 +1,268 @@ +--- +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 +When using **Apache Iceberg tables** in a **Flink streaming environment**, it's important to automate table maintenance operations such as `snapshot expiration`, `small file compaction`, and `orphan file cleanup`. + +Previously, these maintenance tasks were only available through **Iceberg Spark Actions**, requiring a separate Spark cluster. However, maintaining **Spark infrastructure** just for table optimization adds **complexity** and **operational overhead**. + +The `TableMaintenance` API in **Apache Iceberg** enables **Flink jobs** to execute these maintenance tasks **natively** within the same streaming job or as an independent Flink job, avoiding the need for external systems. This approach simplifies **architecture**, reduces **costs**, and improves **automation**. + +## Quick Start +Here's a simple example that sets up automated maintenance for an Iceberg table. + +```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 | Review Comment: May be `Maximum number of snapshots checked when started at the first time. Only available when the change stream is not provided` ? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For additional commands, e-mail: issues-h...@iceberg.apache.org
