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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@ package org.apache.spark.sql.connect.client.jdbc

import java.sql.{Array => _, _}

import org.apache.spark.sql.connect.client.SparkResult

class SparkConnectStatement(conn: SparkConnectConnection) extends Statement {

private var operationId: String = _
Expand Down Expand Up @@ -49,33 +51,51 @@ class SparkConnectStatement(conn: SparkConnectConnection) extends Statement {
}

override def executeQuery(sql: String): ResultSet = {
checkOpen()

val df = conn.spark.sql(sql)
val sparkResult = df.collectResult()
operationId = sparkResult.operationId
resultSet = new SparkConnectResultSet(sparkResult, this)
resultSet
val hasResultSet = execute(sql)
if (hasResultSet) {
assert(resultSet != null)
resultSet
} else {
throw new SQLException("The query does not produce a ResultSet.")
}
}

override def executeUpdate(sql: String): Int = {
checkOpen()

val df = conn.spark.sql(sql)
val sparkResult = df.collectResult()
operationId = sparkResult.operationId
resultSet = null
val hasResultSet = execute(sql)
if (hasResultSet) {
// user are not expected to access the result set in this case,
// we must close it to avoid memory leak.
resultSet.close()
throw new SQLException("The query produces a ResultSet.")
} else {
assert(resultSet == null)
getUpdateCount
}
}

// always return 0 because affected rows is not supported yet
0
private def hasResultSet(sparkResult: SparkResult[_]): Boolean = {
// suppose this works in most cases
sparkResult.schema.length > 0
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I didn't find a counterexample after a quick thought, please let me know if you have a more reliable approach

}

override def execute(sql: String): Boolean = {
checkOpen()

// always perform executeQuery and reture a ResultSet
executeQuery(sql)
true
// stmt can be reused to exeute more than one queries,
// reset before executinng new query
operationId = null
resultSet = null

val df = conn.spark.sql(sql)
val sparkResult = df.collectResult()
operationId = sparkResult.operationId
if (hasResultSet(sparkResult)) {
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I checked some well-known JDBC drivers, and the implementation can be classified into:

  • have a simple JDBC driver-side SQL parser to classify SQL type, e.g., DML, DDL, and justify by the SQL type whether it will return result sets
  • Trino does this better, the server sets the query type in the analyzing phase and returns such info to the client before execution.
  • blindly execute the queries and check the returned result sets

here we use the last approach.

resultSet = new SparkConnectResultSet(sparkResult, this)
true
} else {
sparkResult.close()
false
}
}

override def getResultSet: ResultSet = {
Expand Down Expand Up @@ -123,8 +143,15 @@ class SparkConnectStatement(conn: SparkConnectConnection) extends Statement {
override def setCursorName(name: String): Unit =
throw new SQLFeatureNotSupportedException

override def getUpdateCount: Int =
throw new SQLFeatureNotSupportedException
override def getUpdateCount: Int = {
checkOpen()

if (resultSet != null) {
-1
} else {
0 // always return 0 because affected rows is not supported yet
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this can not be supported soon because it requires non-trivial work on the classic sql module to add metrics for all data writing commands and modify the connect protocol to retrieve them back to the client.

}
}

override def getMoreResults: Boolean =
throw new SQLFeatureNotSupportedException
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,77 @@
/*
* 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.connect.client.jdbc

import java.sql.{Array => _, _}

import scala.util.Using

import org.apache.spark.sql.connect.client.jdbc.test.JdbcHelper
import org.apache.spark.sql.connect.test.{ConnectFunSuite, RemoteSparkSession, SQLHelper}

class SparkConnectStatementSuite extends ConnectFunSuite with RemoteSparkSession
with JdbcHelper with SQLHelper {

override def jdbcUrl: String = s"jdbc:sc://localhost:$serverPort"

test("returned result set and update count of execute* methods") {
withTable("t1", "t2", "t3") {
withStatement { stmt =>
// CREATE TABLE
assert(!stmt.execute("CREATE TABLE t1 (id INT) USING Parquet"))
assert(stmt.getUpdateCount === 0)
assert(stmt.getResultSet === null)

intercept[SQLException] {
stmt.executeQuery("CREATE TABLE t2 (id INT) USING Parquet")
}

assert(stmt.executeUpdate("CREATE TABLE t3 (id INT) USING Parquet") === 0)
assert(stmt.getResultSet === null)

// INSERT INTO
assert(!stmt.execute("INSERT INTO t1 VALUES (1)"))
assert(stmt.getUpdateCount === 0)
assert(stmt.getResultSet === null)

intercept[SQLException] {
stmt.executeQuery("INSERT INTO t1 VALUES (1)")
}

assert(stmt.executeUpdate("INSERT INTO t1 VALUES (1)") === 0)
assert(stmt.getResultSet === null)

// SELECT
assert(stmt.execute("SELECT id FROM t1"))
assert(stmt.getUpdateCount === -1)
Using.resource(stmt.getResultSet) { rs =>
assert(rs !== null)
}

Using.resource(stmt.executeQuery("SELECT id FROM t1")) { rs =>
assert(stmt.getUpdateCount === -1)
assert(rs !== null)
}

intercept[SQLException] {
stmt.executeUpdate("SELECT id FROM t1")
}
}
}
}
}