Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/14116#discussion_r70323016
--- 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 --
Ur, actually, I used `PrunedFilteredScan` because I thought`CatalystScan`
is annotated Experimental and no classes extends that trait. Is there any know
troubles with `PrunedFilteredScan`?
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