mccheah commented on a change in pull request #25040: [SPARK-28238][SQL] Implement DESCRIBE TABLE for Data Source V2 Tables. URL: https://github.com/apache/spark/pull/25040#discussion_r302262119
########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DescribeTableExec.scala ########## @@ -0,0 +1,92 @@ +/* + * 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.execution.datasources.v2 + +import scala.collection.JavaConverters._ +import scala.collection.mutable.ArrayBuffer + +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalog.v2.{Identifier, TableCatalog} +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.encoders.RowEncoder +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, GenericRowWithSchema} +import org.apache.spark.sql.catalyst.plans.DescribeTableSchemas +import org.apache.spark.sql.execution.LeafExecNode +import org.apache.spark.sql.sources.v2.Table + +case class DescribeTableExec( + catalog: TableCatalog, + ident: Identifier, + isExtended: Boolean) extends LeafExecNode { + + private val EMPTY_ROW = toCatalystRow("", "", "") + + override def output: Seq[AttributeReference] = DescribeTableSchemas.DESCRIBE_TABLE_ATTRIBUTES + + override protected def doExecute(): RDD[InternalRow] = { + val rows = new ArrayBuffer[InternalRow]() + if (catalog.tableExists(ident)) { + val table = catalog.loadTable(ident) + addSchema(rows, table) + + if (isExtended) { + addPartitioning(rows, table) + addProperties(rows, table) + } + + } else { + rows += toCatalystRow(s"Table $ident does not exist.", "", "") + } + sparkContext.parallelize(rows) + } + + private def addSchema(rows: ArrayBuffer[InternalRow], table: Table): Unit = { + rows ++= table.schema.map{ column => + toCatalystRow( + column.name, column.dataType.simpleString, column.getComment().getOrElse("")) + } + } + + private def addPartitioning(rows: ArrayBuffer[InternalRow], table: Table): Unit = { + rows += EMPTY_ROW + rows += toCatalystRow(" Partitioning", "", "") + rows += toCatalystRow("--------------", "", "") + if (table.partitioning.isEmpty) { + rows += toCatalystRow("Not partitioned", "", "") + } else { + rows ++= table.partitioning.zipWithIndex.map { + case (transform, index) => toCatalystRow(s"Part $index", transform.describe(), "") + } + } + } + + private def addProperties(rows: ArrayBuffer[InternalRow], table: Table): Unit = { + rows += EMPTY_ROW + rows += toCatalystRow(" Table Property", " Value", "") + rows += toCatalystRow("----------------", "-------", "") + rows ++= table.properties.asScala.toList.sortBy(_._1).map { + case (key, value) => toCatalystRow(key, value, "") + } + } + + private def toCatalystRow(strs: String*): InternalRow = { + val encoder = RowEncoder(DescribeTableSchemas.DESCRIBE_TABLE_SCHEMA).resolveAndBind() Review comment: Sort of - couple of questions: - Is `RowEncoder` thread-safe? - I noticed if I create `RowEncoder` but immediately `resolveAndBind` it, and reuse the resolved encoder, the tests break as the describe returns incorrect rows. Presumably there's some kind of reused memory leak here. I didn't look into it that thoroughly - think we can just reuse the unresolved encoder and `resolveAndBind` before creating each row. ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
