Github user hvanhovell commented on a diff in the pull request: https://github.com/apache/spark/pull/14116#discussion_r70253855 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/systemcatalog/InformationSchema.scala --- @@ -0,0 +1,336 @@ +/* + * 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.systemcatalog + +import java.sql.{Date, Timestamp} + +import scala.collection.mutable.ArrayBuffer + +import org.apache.commons.lang3.StringUtils + +import org.apache.spark.rdd.RDD +import org.apache.spark.sql._ +import org.apache.spark.sql.catalyst.dsl.plans._ +import org.apache.spark.sql.catalyst.expressions.Alias +import org.apache.spark.sql.catalyst.plans.logical.Project +import org.apache.spark.sql.execution.datasources._ +import org.apache.spark.sql.sources._ +import org.apache.spark.sql.types._ + +/** + * INFORMATION_SCHEMA is a database consisting views which provide information about all of the + * tables, views, columns in a database. + */ +object InformationSchema { + val INFORMATION_SCHEMA = "information_schema" + /** + * Register INFORMATION_SCHEMA database. + */ + def registerInformationSchema(sparkSession: SparkSession): Unit = { + sparkSession.sql(s"CREATE DATABASE IF NOT EXISTS $INFORMATION_SCHEMA") + registerView(sparkSession, new DatabasesRelationProvider, Seq("schemata", "databases")) + registerView(sparkSession, new TablesRelationProvider, Seq("tables")) + registerView(sparkSession, new ViewsRelationProvider, Seq("views")) + registerView(sparkSession, new ColumnsRelationProvider, Seq("columns")) + registerView(sparkSession, new SessionVariablesRelationProvider, Seq("session_variables")) + } + + /** + * Register a INFORMATION_SCHEMA relation provider as a temporary view of Spark Catalog. + */ + private def registerView( + sparkSession: SparkSession, + relationProvider: SchemaRelationProvider, + names: Seq[String]) { + val plan = + LogicalRelation(relationProvider.createRelation(sparkSession.sqlContext, null, null)).analyze + val projectList = plan.output.zip(plan.schema).map { + case (attr, col) => Alias(attr, col.name)() + } + sparkSession.sessionState.executePlan(Project(projectList, plan)) + for (name <- names) { + // TODO(dongjoon): This is a hack to give a database concept for Spark temporary views. + // We should generalize this later. + sparkSession.sessionState.catalog.createTempView(s"$INFORMATION_SCHEMA.$name", + plan, overrideIfExists = true) + } + } + + /** + * Compile filter array into single string condition. + */ + private[systemcatalog] def getConditionExpressionString(filters: Array[Filter]): String = { + val str = filters.flatMap(InformationSchema.compileFilter).map(p => s"($p)").mkString(" AND ") + if (str.length == 0) "TRUE" else str + } + + /** + * Convert filter into string expression. + */ + private[systemcatalog] def compileFilter(f: Filter): Option[String] = { + Option(f match { + case EqualTo(attr, value) => s"$attr = ${compileValue(value)}" + case EqualNullSafe(attr, value) => + s"(NOT ($attr != ${compileValue(value)} OR $attr IS NULL OR " + + s"${compileValue(value)} IS NULL) OR " + + s"($attr IS NULL AND ${compileValue(value)} IS NULL))" + case LessThan(attr, value) => s"$attr < ${compileValue(value)}" + case GreaterThan(attr, value) => s"$attr > ${compileValue(value)}" + case LessThanOrEqual(attr, value) => s"$attr <= ${compileValue(value)}" + case GreaterThanOrEqual(attr, value) => s"$attr >= ${compileValue(value)}" + case IsNull(attr) => s"$attr IS NULL" + case IsNotNull(attr) => s"$attr IS NOT NULL" + case StringStartsWith(attr, value) => s"${attr} LIKE '${value}%'" + case StringEndsWith(attr, value) => s"${attr} LIKE '%${value}'" + case StringContains(attr, value) => s"${attr} LIKE '%${value}%'" + case In(attr, value) => s"$attr IN (${compileValue(value)})" + case Not(f) => compileFilter(f).map(p => s"(NOT ($p))").orNull + case Or(f1, f2) => + val or = Seq(f1, f2).flatMap(compileFilter(_)) + if (or.size == 2) { + or.map(p => s"($p)").mkString(" OR ") + } else { + null + } + case And(f1, f2) => + val and = Seq(f1, f2).flatMap(compileFilter(_)) + if (and.size == 2) { + and.map(p => s"($p)").mkString(" AND ") + } else { + null + } + case _ => null + }) + } + + /** + * Converts value into string expression. + */ + private[systemcatalog] def compileValue(value: Any): Any = value match { + case s: String => + val escapedValue = if (s == null) null else StringUtils.replace(s, "'", "''") + s"'$escapedValue'" + case t: Timestamp => "'" + t + "'" + case d: Date => "'" + d + "'" + case a: Array[Any] => a.map(compileValue).mkString(", ") + case _ => value + } +} + +/** + * Provides DATABASES relation consisting all databases. + */ +private class DatabasesRelationProvider extends SchemaRelationProvider { + override def createRelation( + sqlContext: SQLContext, + parameters: Map[String, String], + schema: StructType): BaseRelation = { + val sparkSession = sqlContext.sparkSession + + new BaseRelation with PrunedFilteredScan { --- End diff -- We could also use CatalystScan here. That could save us little trouble.
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