akashrn5 commented on a change in pull request #3938:
URL: https://github.com/apache/carbondata/pull/3938#discussion_r491814518
##########
File path:
integration/spark/src/main/scala/org/apache/spark/sql/execution/strategy/DDLHelper.scala
##########
@@ -398,9 +398,7 @@ object DDLHelper {
}
def showTables(showTablesCommand: ShowTablesCommand): Seq[SparkPlan] = {
Review comment:
is this method really required? can't we just directly call the command
class from `DDLStrategy `class? Why to add an intermediate method?
##########
File path:
integration/spark/src/main/scala/org/apache/spark/sql/execution/command/table/CarbonShowTablesCommand.scala
##########
@@ -18,35 +18,23 @@
package org.apache.spark.sql.execution.command.table
import org.apache.spark.sql.{Row, SparkSession}
-import org.apache.spark.sql.catalyst.TableIdentifier
-import org.apache.spark.sql.catalyst.expressions.{Attribute,
AttributeReference}
-import org.apache.spark.sql.execution.command.MetadataCommand
-import org.apache.spark.sql.types.{BooleanType, StringType}
+import org.apache.spark.sql.catalyst.expressions.Attribute
+import org.apache.spark.sql.execution.command.{MetadataCommand,
ShowTablesCommand}
-private[sql] case class CarbonShowTablesCommand ( databaseName: Option[String],
- tableIdentifierPattern: Option[String]) extends MetadataCommand{
+private[sql] case class CarbonShowTablesCommand(showTablesCommand:
ShowTablesCommand)
+ extends MetadataCommand {
- // The result of SHOW TABLES has three columns: database, tableName and
isTemporary.
- override val output: Seq[Attribute] = {
- AttributeReference("database", StringType, nullable = false)() ::
- AttributeReference("tableName", StringType, nullable = false)() ::
- AttributeReference("isTemporary", BooleanType, nullable = false)() :: Nil
- }
+ override val output: Seq[Attribute] = showTablesCommand.output
override def processMetadata(sparkSession: SparkSession): Seq[Row] = {
- // Since we need to return a Seq of rows, we will call getTables directly
- // instead of calling tables in sparkSession.
- val catalog = sparkSession.sessionState.catalog
- val db = databaseName.getOrElse(catalog.getCurrentDatabase)
- val tables =
- tableIdentifierPattern.map(catalog.listTables(db,
_)).getOrElse(catalog.listTables(db))
+ val rows = showTablesCommand.run(sparkSession)
val externalCatalog = sparkSession.sharedState.externalCatalog
// this method checks whether the table is mainTable or MV based on
property "isVisible"
- def isMainTable(tableIdent: TableIdentifier) = {
+ def isMainTable(db: String, table: String) = {
Review comment:
move this method after line 46 and also add a comment inside
implementation saying what we filter here.
##########
File path:
integration/spark/src/test/scala/org/apache/carbondata/spark/testsuite/ShowTable/TestShowTable.scala
##########
@@ -0,0 +1,94 @@
+/*
+ * 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.carbondata.spark.testsuite.ShowTable
+
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.test.util.QueryTest
+import org.scalatest.{BeforeAndAfterAll, BeforeAndAfterEach}
+
+import
org.apache.carbondata.common.exceptions.sql.MalformedIndexCommandException
+
+/**
+ * Test class for show tables.
+ */
+class TestShowTable extends QueryTest with BeforeAndAfterAll with
BeforeAndAfterEach {
+ val dbName = "testshowtable"
+ override def beforeAll: Unit = {
+ sql(s"drop database if exists $dbName cascade")
+ sql(s"create database $dbName")
+ sql(s"use $dbName")
+ }
+
+ test("test show tables") {
+ sql("create table employee(id string, name string) stored as carbondata")
+ sql("create table employee_part(name string) partitioned by (grade int)")
+ sql("create index employee_si on table employee(name) as 'carbondata'")
+ sql("create materialized view employee_mv as select name from employee
group by name")
+ val df = sql("show tables").toDF
Review comment:
combine rows 41 and 42 and direct do `.collect()` on sql
##########
File path:
integration/spark/src/test/scala/org/apache/carbondata/spark/testsuite/ShowTable/TestShowTable.scala
##########
@@ -0,0 +1,94 @@
+/*
+ * 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.carbondata.spark.testsuite.ShowTable
+
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.test.util.QueryTest
+import org.scalatest.{BeforeAndAfterAll, BeforeAndAfterEach}
+
+import
org.apache.carbondata.common.exceptions.sql.MalformedIndexCommandException
+
+/**
+ * Test class for show tables.
+ */
+class TestShowTable extends QueryTest with BeforeAndAfterAll with
BeforeAndAfterEach {
+ val dbName = "testshowtable"
+ override def beforeAll: Unit = {
+ sql(s"drop database if exists $dbName cascade")
+ sql(s"create database $dbName")
+ sql(s"use $dbName")
+ }
+
+ test("test show tables") {
+ sql("create table employee(id string, name string) stored as carbondata")
+ sql("create table employee_part(name string) partitioned by (grade int)")
+ sql("create index employee_si on table employee(name) as 'carbondata'")
+ sql("create materialized view employee_mv as select name from employee
group by name")
+ val df = sql("show tables").toDF
+ val rows = df.collect()
+ val schema = rows(0).schema
+ assert(schema.length == 3)
+ assert(schema(0).name.equals("database"))
+ assert(schema(1).name.equals("tableName"))
+ assert(schema(2).name.equals("isTemporary"))
+ // show tables query can return views as well. Just validate if expected
rows are present
+ // and unexpected rows are not present.
+ val expectedRows = Seq(Row(dbName, "employee", false),
+ Row(dbName, "employee_part", false),
+ Row(dbName, "employee_si", false))
+ val expectedRowsDF = sqlContext.sparkSession
+ .createDataFrame(sqlContext.sparkContext.makeRDD[Row](expectedRows),
schema)
+ checkAnswer(df.intersect(expectedRowsDF), expectedRows)
+ // check if mv table is not present
+ val notExpectedRows = Seq(Row(dbName, "employee_mv", false))
+ val notExpectedRowsDF = sqlContext.sparkSession
+ .createDataFrame(sqlContext.sparkContext.makeRDD[Row](notExpectedRows),
schema)
+ assert(df.intersect(notExpectedRowsDF).count() == 0)
+ }
+
+ test("test show table extended like") {
+ sql("create table employee(id string, name string) stored as carbondata")
Review comment:
can you add one query for non carbon table also?
##########
File path:
integration/spark/src/test/scala/org/apache/carbondata/spark/testsuite/ShowTable/TestShowTable.scala
##########
@@ -0,0 +1,94 @@
+/*
+ * 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.carbondata.spark.testsuite.ShowTable
+
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.test.util.QueryTest
+import org.scalatest.{BeforeAndAfterAll, BeforeAndAfterEach}
+
+import
org.apache.carbondata.common.exceptions.sql.MalformedIndexCommandException
+
+/**
+ * Test class for show tables.
+ */
+class TestShowTable extends QueryTest with BeforeAndAfterAll with
BeforeAndAfterEach {
+ val dbName = "testshowtable"
+ override def beforeAll: Unit = {
+ sql(s"drop database if exists $dbName cascade")
+ sql(s"create database $dbName")
+ sql(s"use $dbName")
+ }
+
+ test("test show tables") {
+ sql("create table employee(id string, name string) stored as carbondata")
+ sql("create table employee_part(name string) partitioned by (grade int)")
+ sql("create index employee_si on table employee(name) as 'carbondata'")
+ sql("create materialized view employee_mv as select name from employee
group by name")
+ val df = sql("show tables").toDF
+ val rows = df.collect()
+ val schema = rows(0).schema
+ assert(schema.length == 3)
+ assert(schema(0).name.equals("database"))
+ assert(schema(1).name.equals("tableName"))
+ assert(schema(2).name.equals("isTemporary"))
+ // show tables query can return views as well. Just validate if expected
rows are present
+ // and unexpected rows are not present.
+ val expectedRows = Seq(Row(dbName, "employee", false),
+ Row(dbName, "employee_part", false),
+ Row(dbName, "employee_si", false))
+ val expectedRowsDF = sqlContext.sparkSession
Review comment:
no need to create the dataframes, just can use `checkanswer` APIs to
provide `SQL `and `Seg[Rows[]]`, please modify all places
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