XiaoHongbo-Hope commented on code in PR #6612: URL: https://github.com/apache/paimon/pull/6612#discussion_r2538315335
########## paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/RescaleProcedure.java: ########## @@ -0,0 +1,245 @@ +/* + * 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. + */ + +package org.apache.paimon.spark.procedure; + +import org.apache.paimon.CoreOptions; +import org.apache.paimon.Snapshot; +import org.apache.paimon.manifest.ManifestEntry; +import org.apache.paimon.partition.PartitionPredicate; +import org.apache.paimon.spark.commands.PaimonSparkWriter; +import org.apache.paimon.spark.util.ScanPlanHelper$; +import org.apache.paimon.spark.utils.SparkProcedureUtils; +import org.apache.paimon.table.BucketMode; +import org.apache.paimon.table.FileStoreTable; +import org.apache.paimon.table.source.DataSplit; +import org.apache.paimon.table.source.snapshot.SnapshotReader; +import org.apache.paimon.utils.StringUtils; + +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.PaimonUtils; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.catalyst.InternalRow; +import org.apache.spark.sql.connector.catalog.Identifier; +import org.apache.spark.sql.connector.catalog.TableCatalog; +import org.apache.spark.sql.execution.datasources.v2.DataSourceV2Relation; +import org.apache.spark.sql.types.DataTypes; +import org.apache.spark.sql.types.Metadata; +import org.apache.spark.sql.types.StructField; +import org.apache.spark.sql.types.StructType; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import javax.annotation.Nullable; + +import java.util.HashMap; +import java.util.Iterator; +import java.util.List; +import java.util.Map; +import java.util.Optional; + +import static org.apache.paimon.utils.Preconditions.checkArgument; +import static org.apache.spark.sql.types.DataTypes.IntegerType; +import static org.apache.spark.sql.types.DataTypes.StringType; + +/** + * Rescale procedure. Usage: + * + * <pre><code> + * CALL sys.rescale(table => 'databaseName.tableName', [bucket_num => 16], [partitions => 'dt=20250217,hh=08;dt=20250218,hh=08'], [where => 'dt>20250217'], [scan_parallelism => 8], [sink_parallelism => 16]) + * </code></pre> + */ +public class RescaleProcedure extends BaseProcedure { + + private static final Logger LOG = LoggerFactory.getLogger(RescaleProcedure.class); + + private static final ProcedureParameter[] PARAMETERS = + new ProcedureParameter[] { + ProcedureParameter.required("table", StringType), + ProcedureParameter.optional("bucket_num", IntegerType), + ProcedureParameter.optional("partitions", StringType), + ProcedureParameter.optional("where", StringType), + ProcedureParameter.optional("scan_parallelism", IntegerType), + ProcedureParameter.optional("sink_parallelism", IntegerType), + }; + + private static final StructType OUTPUT_TYPE = + new StructType( + new StructField[] { + new StructField("result", DataTypes.BooleanType, true, Metadata.empty()) + }); + + protected RescaleProcedure(TableCatalog tableCatalog) { + super(tableCatalog); + } + + @Override + public ProcedureParameter[] parameters() { + return PARAMETERS; + } + + @Override + public StructType outputType() { + return OUTPUT_TYPE; + } + + @Override + public InternalRow[] call(InternalRow args) { + Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name()); + Integer bucketNum = args.isNullAt(1) ? null : args.getInt(1); + String partitions = blank(args, 2) ? null : args.getString(2); + String where = blank(args, 3) ? null : args.getString(3); + Integer scanParallelism = args.isNullAt(4) ? null : args.getInt(4); + Integer sinkParallelism = args.isNullAt(5) ? null : args.getInt(5); + + checkArgument( + partitions == null || where == null, + "partitions and where cannot be used together."); + String finalWhere = partitions != null ? SparkProcedureUtils.toWhere(partitions) : where; + + return modifyPaimonTable( + tableIdent, + table -> { + checkArgument(table instanceof FileStoreTable); + FileStoreTable fileStoreTable = (FileStoreTable) table; + + Optional<Snapshot> optionalSnapshot = fileStoreTable.latestSnapshot(); + if (!optionalSnapshot.isPresent()) { + throw new IllegalArgumentException( + "Table " + + table.fullName() + + " has no snapshot. No need to rescale."); + } + Snapshot snapshot = optionalSnapshot.get(); + + // If someone commits while the rescale job is running, this commit will be + // lost. + // So we use strict mode to make sure nothing is lost. + Map<String, String> dynamicOptions = new HashMap<>(); + dynamicOptions.put( + CoreOptions.COMMIT_STRICT_MODE_LAST_SAFE_SNAPSHOT.key(), + String.valueOf(snapshot.id())); + fileStoreTable = fileStoreTable.copy(dynamicOptions); + + DataSourceV2Relation relation = createRelation(tableIdent); + PartitionPredicate partitionPredicate = + SparkProcedureUtils.convertToPartitionPredicate( + finalWhere, + fileStoreTable.schema().logicalPartitionType(), + spark(), + relation); + + int finalBucketNum; + if (bucketNum == null) { + checkArgument( + fileStoreTable.coreOptions().bucket() != BucketMode.POSTPONE_BUCKET, + "When rescaling postpone bucket tables, you must provide the resulting bucket number."); + finalBucketNum = + currentBucketNum(fileStoreTable, snapshot, partitionPredicate); + } else { + finalBucketNum = bucketNum; + } + + int finalScanParallelism = + scanParallelism == null ? finalBucketNum : scanParallelism; + + execute( + fileStoreTable, + finalBucketNum, + partitionPredicate, + finalScanParallelism, + sinkParallelism, + tableIdent); + + InternalRow internalRow = newInternalRow(true); + return new InternalRow[] {internalRow}; + }); + } + + private void execute( + FileStoreTable table, + int bucketNum, + PartitionPredicate partitionPredicate, + int scanParallelism, + @Nullable Integer sinkParallelism, + Identifier tableIdent) { + DataSourceV2Relation relation = createRelation(tableIdent); + + SnapshotReader snapshotReader = table.newSnapshotReader(); + if (partitionPredicate != null) { + snapshotReader = snapshotReader.withPartitionFilter(partitionPredicate); + } + List<DataSplit> dataSplits = snapshotReader.read().dataSplits(); + + if (dataSplits.isEmpty()) { + LOG.info("No data splits found for the specified partition. No need to rescale."); + return; + } + + Dataset<Row> datasetForRead = + PaimonUtils.createDataset( + spark(), + ScanPlanHelper$.MODULE$.createNewScanPlan( + dataSplits.toArray(new DataSplit[0]), relation)); + + Dataset<Row> datasetForWrite = datasetForRead.repartition(scanParallelism); + + Map<String, String> bucketOptions = new HashMap<>(table.options()); + bucketOptions.put(CoreOptions.BUCKET.key(), String.valueOf(bucketNum)); Review Comment: > Do we need to configure this when using postpone bucket updated -- 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]
