grundprinzip commented on code in PR #39078: URL: https://github.com/apache/spark/pull/39078#discussion_r1053333910
########## connector/connect/client/src/main/scala/org/apache/spark/sql/connect/client/SparkSession.scala: ########## @@ -0,0 +1,106 @@ +/* + * 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 + +import org.apache.arrow.memory.RootAllocator + +import org.apache.spark.SPARK_VERSION +import org.apache.spark.connect.proto + + +class SparkSession(private val userContext: proto.UserContext) extends AutoCloseable { + + private[this] val allocator = new RootAllocator() + + /** + * The version of Spark on which this application is running. + */ + def version: String = SPARK_VERSION + + /** + * Returns a `DataFrame` with no rows or columns. + * + * @since 3.4.0 + */ + @transient + lazy val emptyDataFrame: Dataset = newDataset { builder => + builder.getLocalRelationBuilder + } + + /** + * Creates a [[Dataset]] with a single `LongType` column named `id`, containing elements + * in a range from `start` to `end` (exclusive) with a step value, with partition number + * specified. + * + * @since 3.4.0 + */ + def range(start: Long, end: Long, step: Long, numPartitions: Int): Dataset = { + range(start, end, step, Option(numPartitions)) + } + + private def range(start: Long, end: Long, step: Long, numPartitions: Option[Int]): Dataset = { + newDataset { builder => + val rangeBuilder = builder.getRangeBuilder + .setStart(start) + .setEnd(end) + .setStep(step) + numPartitions.foreach(rangeBuilder.setNumPartitions) + } + } + + /** + * Executes a SQL query using Spark, returning the result as a `DataFrame`. + * This API eagerly runs DDL/DML commands, but not for SELECT queries. + * + * @since 3.4.0 + */ + def sql(query: String): Dataset = newDataset { builder => + builder.setSql(proto.SQL.newBuilder().setQuery(query)) Review Comment: just as an FYI because we have the same bug in Python. Right now this API actually is not eagerly evaluating the SQL query. -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
