stream2000 commented on code in PR #10120: URL: https://github.com/apache/hudi/pull/10120#discussion_r1402852595
########## hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/procedures/ShowMetadataTableColumnStatsProcedure.scala: ########## @@ -0,0 +1,169 @@ +/* + * 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.spark.sql.hudi.command.procedures + +import org.apache.avro.generic.IndexedRecord +import org.apache.hadoop.fs.{FileStatus, Path} +import org.apache.hudi.avro.model._ +import org.apache.hudi.client.common.HoodieSparkEngineContext +import org.apache.hudi.common.config.HoodieMetadataConfig +import org.apache.hudi.common.data.HoodieData +import org.apache.hudi.common.fs.FSUtils +import org.apache.hudi.common.model.FileSlice +import org.apache.hudi.common.table.timeline.{HoodieDefaultTimeline, HoodieInstant} +import org.apache.hudi.common.table.view.HoodieTableFileSystemView +import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver} +import org.apache.hudi.common.util.{Option => HOption} +import org.apache.hudi.exception.HoodieException +import org.apache.hudi.metadata.HoodieTableMetadata +import org.apache.hudi.{AvroConversionUtils, ColumnStatsIndexSupport} +import org.apache.spark.internal.Logging +import org.apache.spark.sql.Row +import org.apache.spark.sql.types.{DataTypes, Metadata, StructField, StructType} + +import java.util +import java.util.function.{Function, Supplier} +import scala.collection.{JavaConversions, mutable} +import scala.jdk.CollectionConverters.{asScalaBufferConverter, asScalaIteratorConverter} + + +class ShowMetadataTableColumnStatsProcedure extends BaseProcedure with ProcedureBuilder with Logging { + private val PARAMETERS = Array[ProcedureParameter]( + ProcedureParameter.required(0, "table", DataTypes.StringType), + ProcedureParameter.optional(1, "partition", DataTypes.StringType), + ProcedureParameter.optional(2, "targetColumns", DataTypes.StringType) + ) + + private val OUTPUT_TYPE = new StructType(Array[StructField]( + StructField("file_name", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("column_name", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("min_value", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("max_value", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("null_num", DataTypes.LongType, nullable = true, Metadata.empty) + )) + + def parameters: Array[ProcedureParameter] = PARAMETERS + + def outputType: StructType = OUTPUT_TYPE + + override def call(args: ProcedureArgs): Seq[Row] = { + super.checkArgs(PARAMETERS, args) + + val table = getArgValueOrDefault(args, PARAMETERS(0)) + val partitions = getArgValueOrDefault(args, PARAMETERS(1)).getOrElse("").toString + val partitionsSeq = partitions.split(",").filter(_.nonEmpty).toSeq + + val targetColumns = getArgValueOrDefault(args, PARAMETERS(2)).getOrElse("").toString + val targetColumnsSeq = targetColumns.split(",").toSeq + val basePath = getBasePath(table) + val metadataConfig = HoodieMetadataConfig.newBuilder + .enable(true) + .build + val metaClient = HoodieTableMetaClient.builder.setConf(jsc.hadoopConfiguration()).setBasePath(basePath).build + val schemaUtil = new TableSchemaResolver(metaClient) + val schema = AvroConversionUtils.convertAvroSchemaToStructType(schemaUtil.getTableAvroSchema) + val columnStatsIndex = new ColumnStatsIndexSupport(spark, schema, metadataConfig, metaClient) Review Comment: We should use `org.apache.hudi.metadata.BaseTableMetadata#getColumnStats` to load colunm stats instead of calling columnStatsIndex directly. ########## hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/procedures/ShowMetadataTableColumnStatsProcedure.scala: ########## @@ -0,0 +1,169 @@ +/* + * 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.spark.sql.hudi.command.procedures + +import org.apache.avro.generic.IndexedRecord +import org.apache.hadoop.fs.{FileStatus, Path} +import org.apache.hudi.avro.model._ +import org.apache.hudi.client.common.HoodieSparkEngineContext +import org.apache.hudi.common.config.HoodieMetadataConfig +import org.apache.hudi.common.data.HoodieData +import org.apache.hudi.common.fs.FSUtils +import org.apache.hudi.common.model.FileSlice +import org.apache.hudi.common.table.timeline.{HoodieDefaultTimeline, HoodieInstant} +import org.apache.hudi.common.table.view.HoodieTableFileSystemView +import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver} +import org.apache.hudi.common.util.{Option => HOption} +import org.apache.hudi.exception.HoodieException +import org.apache.hudi.metadata.HoodieTableMetadata +import org.apache.hudi.{AvroConversionUtils, ColumnStatsIndexSupport} +import org.apache.spark.internal.Logging +import org.apache.spark.sql.Row +import org.apache.spark.sql.types.{DataTypes, Metadata, StructField, StructType} + +import java.util +import java.util.function.{Function, Supplier} +import scala.collection.{JavaConversions, mutable} +import scala.jdk.CollectionConverters.{asScalaBufferConverter, asScalaIteratorConverter} + + +class ShowMetadataTableColumnStatsProcedure extends BaseProcedure with ProcedureBuilder with Logging { + private val PARAMETERS = Array[ProcedureParameter]( + ProcedureParameter.required(0, "table", DataTypes.StringType), + ProcedureParameter.optional(1, "partition", DataTypes.StringType), + ProcedureParameter.optional(2, "targetColumns", DataTypes.StringType) + ) + + private val OUTPUT_TYPE = new StructType(Array[StructField]( + StructField("file_name", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("column_name", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("min_value", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("max_value", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("null_num", DataTypes.LongType, nullable = true, Metadata.empty) + )) + + def parameters: Array[ProcedureParameter] = PARAMETERS + + def outputType: StructType = OUTPUT_TYPE + + override def call(args: ProcedureArgs): Seq[Row] = { + super.checkArgs(PARAMETERS, args) + + val table = getArgValueOrDefault(args, PARAMETERS(0)) + val partitions = getArgValueOrDefault(args, PARAMETERS(1)).getOrElse("").toString + val partitionsSeq = partitions.split(",").filter(_.nonEmpty).toSeq + + val targetColumns = getArgValueOrDefault(args, PARAMETERS(2)).getOrElse("").toString + val targetColumnsSeq = targetColumns.split(",").toSeq + val basePath = getBasePath(table) + val metadataConfig = HoodieMetadataConfig.newBuilder + .enable(true) + .build + val metaClient = HoodieTableMetaClient.builder.setConf(jsc.hadoopConfiguration()).setBasePath(basePath).build + val schemaUtil = new TableSchemaResolver(metaClient) + val schema = AvroConversionUtils.convertAvroSchemaToStructType(schemaUtil.getTableAvroSchema) + val columnStatsIndex = new ColumnStatsIndexSupport(spark, schema, metadataConfig, metaClient) + val colStatsRecords: HoodieData[HoodieMetadataColumnStats] = columnStatsIndex.loadColumnStatsIndexRecords(targetColumnsSeq, shouldReadInMemory = false) + val fsView = buildFileSystemView(table) + val allFileSlices: Set[FileSlice] = { + if (partitionsSeq.isEmpty) { + val engineCtx = new HoodieSparkEngineContext(jsc) + val metaTable = HoodieTableMetadata.create(engineCtx, metadataConfig, basePath) + metaTable.getAllPartitionPaths + .asScala + .flatMap(path => fsView.getLatestFileSlices(path).iterator().asScala) + .toSet + } else { + partitionsSeq + .flatMap(partition => fsView.getLatestFileSlices(partition).iterator().asScala) + .toSet + } + } + + val allFileNames: Set[String] = allFileSlices.map(_.getBaseFile.get().getFileName) + + val rows = mutable.ListBuffer[Row]() + colStatsRecords.collectAsList().asScala + .filter(c => allFileNames.contains(c.getFileName)) + .foreach { c => + rows += Row(c.getFileName, c.getColumnName, getColumnStatsValue(c.getMinValue), + getColumnStatsValue(c.getMaxValue), c.getNullCount.longValue()) + } + + rows.toList + } + + private def getColumnStatsValue(stats_value: Any): String = { + stats_value match { + case _: IntWrapper | + _: BooleanWrapper | + _: DateWrapper | + _: DoubleWrapper | + _: FloatWrapper | + _: LongWrapper | + _: StringWrapper | + _: TimeMicrosWrapper | + _: TimestampMicrosWrapper => + String.valueOf(stats_value.asInstanceOf[IndexedRecord].get(0)) + case _: BytesWrapper => + val bytes_value = stats_value.asInstanceOf[BytesWrapper].getValue + util.Arrays.toString(bytes_value.array()) + case _: DecimalWrapper => + val decimal_value = stats_value.asInstanceOf[DecimalWrapper].getValue + util.Arrays.toString(decimal_value.array()) + case _ => + throw new HoodieException(s"Unsupported type: ${stats_value.getClass.getSimpleName}") + } + } + + def buildFileSystemView(table: Option[Any]): HoodieTableFileSystemView = { + val basePath = getBasePath(table) + val metaClient = HoodieTableMetaClient.builder.setConf(jsc.hadoopConfiguration()).setBasePath(basePath).build + val fs = metaClient.getFs + val globPath = s"$basePath/*/*/*" Review Comment: Should we make the local variable `globPath` a variable that user can pass in? Or we can just remove it and create an empty filesystem view instead. ########## hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/procedures/ShowMetadataTableColumnStatsProcedure.scala: ########## @@ -0,0 +1,169 @@ +/* + * 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.spark.sql.hudi.command.procedures + +import org.apache.avro.generic.IndexedRecord +import org.apache.hadoop.fs.{FileStatus, Path} +import org.apache.hudi.avro.model._ +import org.apache.hudi.client.common.HoodieSparkEngineContext +import org.apache.hudi.common.config.HoodieMetadataConfig +import org.apache.hudi.common.data.HoodieData +import org.apache.hudi.common.fs.FSUtils +import org.apache.hudi.common.model.FileSlice +import org.apache.hudi.common.table.timeline.{HoodieDefaultTimeline, HoodieInstant} +import org.apache.hudi.common.table.view.HoodieTableFileSystemView +import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver} +import org.apache.hudi.common.util.{Option => HOption} +import org.apache.hudi.exception.HoodieException +import org.apache.hudi.metadata.HoodieTableMetadata +import org.apache.hudi.{AvroConversionUtils, ColumnStatsIndexSupport} +import org.apache.spark.internal.Logging +import org.apache.spark.sql.Row +import org.apache.spark.sql.types.{DataTypes, Metadata, StructField, StructType} + +import java.util +import java.util.function.{Function, Supplier} +import scala.collection.{JavaConversions, mutable} +import scala.jdk.CollectionConverters.{asScalaBufferConverter, asScalaIteratorConverter} + + +class ShowMetadataTableColumnStatsProcedure extends BaseProcedure with ProcedureBuilder with Logging { + private val PARAMETERS = Array[ProcedureParameter]( + ProcedureParameter.required(0, "table", DataTypes.StringType), + ProcedureParameter.optional(1, "partition", DataTypes.StringType), + ProcedureParameter.optional(2, "targetColumns", DataTypes.StringType) + ) + + private val OUTPUT_TYPE = new StructType(Array[StructField]( + StructField("file_name", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("column_name", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("min_value", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("max_value", DataTypes.StringType, nullable = true, Metadata.empty), + StructField("null_num", DataTypes.LongType, nullable = true, Metadata.empty) + )) + + def parameters: Array[ProcedureParameter] = PARAMETERS + + def outputType: StructType = OUTPUT_TYPE + + override def call(args: ProcedureArgs): Seq[Row] = { + super.checkArgs(PARAMETERS, args) + + val table = getArgValueOrDefault(args, PARAMETERS(0)) + val partitions = getArgValueOrDefault(args, PARAMETERS(1)).getOrElse("").toString + val partitionsSeq = partitions.split(",").filter(_.nonEmpty).toSeq + + val targetColumns = getArgValueOrDefault(args, PARAMETERS(2)).getOrElse("").toString + val targetColumnsSeq = targetColumns.split(",").toSeq + val basePath = getBasePath(table) + val metadataConfig = HoodieMetadataConfig.newBuilder + .enable(true) + .build + val metaClient = HoodieTableMetaClient.builder.setConf(jsc.hadoopConfiguration()).setBasePath(basePath).build + val schemaUtil = new TableSchemaResolver(metaClient) + val schema = AvroConversionUtils.convertAvroSchemaToStructType(schemaUtil.getTableAvroSchema) + val columnStatsIndex = new ColumnStatsIndexSupport(spark, schema, metadataConfig, metaClient) + val colStatsRecords: HoodieData[HoodieMetadataColumnStats] = columnStatsIndex.loadColumnStatsIndexRecords(targetColumnsSeq, shouldReadInMemory = false) + val fsView = buildFileSystemView(table) + val allFileSlices: Set[FileSlice] = { + if (partitionsSeq.isEmpty) { + val engineCtx = new HoodieSparkEngineContext(jsc) + val metaTable = HoodieTableMetadata.create(engineCtx, metadataConfig, basePath) + metaTable.getAllPartitionPaths + .asScala + .flatMap(path => fsView.getLatestFileSlices(path).iterator().asScala) + .toSet + } else { + partitionsSeq + .flatMap(partition => fsView.getLatestFileSlices(partition).iterator().asScala) + .toSet + } + } + + val allFileNames: Set[String] = allFileSlices.map(_.getBaseFile.get().getFileName) + + val rows = mutable.ListBuffer[Row]() + colStatsRecords.collectAsList().asScala + .filter(c => allFileNames.contains(c.getFileName)) + .foreach { c => + rows += Row(c.getFileName, c.getColumnName, getColumnStatsValue(c.getMinValue), Review Comment: Will the row sort by column name? I mean, column stats of the same column should be close to each other. -- 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: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
