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/*
* 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.scheduler
import org.apache.spark.{LocalSparkContext, SparkConf, SparkContext, SparkException, SparkFunSuite}
import org.apache.spark.util.{RpcUtils, SerializableBuffer}
class CoarseGrainedSchedulerBackendSuite extends SparkFunSuite with LocalSparkContext {
test("serialized task larger than max RPC message size") {
val conf = new SparkConf
conf.set("spark.rpc.message.maxSize", "1")
conf.set("spark.default.parallelism", "1")
sc = new SparkContext("local-cluster[2, 1, 1024]", "test", conf)
val frameSize = RpcUtils.maxMessageSizeBytes(sc.conf)
val buffer = new SerializableBuffer(java.nio.ByteBuffer.allocate(2 * frameSize))
val larger = sc.parallelize(Seq(buffer))
val thrown = intercept[SparkException] {
larger.collect()
}
assert(thrown.getMessage.contains("using broadcast variables for large values"))
val smaller = sc.parallelize(1 to 4).collect()
assert(smaller.size === 4)
}
}
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