Guosmilesmile commented on code in PR #13771: URL: https://github.com/apache/iceberg/pull/13771#discussion_r2264769824
########## 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 | Review Comment: Can we extract the common configurations belonging to the MaintenanceTaskBuilder, instead of having them appear in each functional configuration separately? ########## 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 | Review Comment: Perhaps "Enable partial progress commits, allowing compacted data files to be committed in batches." would be easier to understand. ########## 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) +``` Review Comment: It would be better to integrate these with the common configuration section provided above. ########## 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: It is not invoked in this way; specific cases can be found here. https://github.com/apache/iceberg/blob/main/flink/v2.0/flink/src/test/java/org/apache/iceberg/flink/sink/TestIcebergSinkCompact.java ########## 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 | Review Comment: Same note as above. ########## 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 | Review Comment: Default value is 5 days ago ########## 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(); Review Comment: I think we do not have a method called `defaultLockFactory`; instead, we need to create a specific LockFactory. ########## 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 Review Comment: Some configurations are still missing from the documentation: minFileSizeBytes maxFileSizeBytes minInputFiles deleteFileThreshold rewriteAll maxFileGroupSizeBytes maxFilesToRewrite filter ########## 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 | Review Comment: We are missing some configurations that have not been added, such as planningWorkerPoolSize and cleanExpiredMetadata. ########## 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 | Review Comment: From my perspective, this part seems a bit strange. How is it used? I can't think of where these configurations come from. ########## 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)) + ) + .append(); +``` + +This approach executes maintenance tasks in the same job as the sink, enabling real-time optimization without running a separate job. + +## Lock Configuration Example + +Iceberg uses a locking mechanism to prevent multiple Flink jobs from performing maintenance on the same table simultaneously. Locks are provided via the TriggerLockFactory and support either JDBC or ZooKeeper backends. + +### JDBC Lock Example +```properties +flink-maintenance.lock.type=jdbc +flink-maintenance.lock.lock-id=catalog.db.table +flink-maintenance.lock.jdbc.uri=jdbc:postgresql://localhost:5432/iceberg +flink-maintenance.lock.jdbc.user=flink +flink-maintenance.lock.jdbc.password=flinkpw +flink-maintenance.lock.jdbc.init-lock-tables=true +``` +JDBC-based locking is recommended for most production environments. + + +### ZooKeeper Lock Example +```properties +flink-maintenance.lock.type=zookeeper +flink-maintenance.lock.zookeeper.uri=zk://zk1:2181,zk2:2181 +flink-maintenance.lock.zookeeper.session-timeout-ms=60000 +flink-maintenance.lock.zookeeper.connection-timeout-ms=15000 +flink-maintenance.lock.zookeeper.max-retries=3 +flink-maintenance.lock.zookeeper.base-sleep-ms=3000 +``` +Use ZooKeeper-based locks only in high-availability or multi-process coordination environments. + + +## Best Practices + +### Resource Management +- Use dedicated slot sharing groups for maintenance tasks +- Set appropriate parallelism based on cluster resources +- Enable checkpointing for fault tolerance + +### Scheduling Strategy +- Avoid too frequent executions with `rateLimit` +- Use `scheduleOnCommitCount` for write-heavy tables +- Use `scheduleOnDataFileCount` for fine-grained control + +### Performance Tuning +- Adjust `deleteBatchSize` based on storage performance +- Enable `partialProgressEnabled` for large rewrite operations +- Set reasonable `maxRewriteBytes` limits + +## Troubleshooting + +### Common Issues + +**OutOfMemoryError during file deletion:** +```java +.deleteBatchSize(500) +``` + +**Lock conflicts:** +```java +.lockCheckDelay(Duration.ofMinutes(1)) +.rateLimit(Duration.ofMinutes(10)) +``` + +**Slow rewrite operations:** +```java +.partialProgressEnabled(true) +.partialProgressMaxCommits(3) +.maxRewriteBytes(1024 * 1024 * 1024) +``` Review Comment: What is the specific scenario here? Providing numerical recommendations directly without detailed reasoning can seem a bit odd. -- 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
