错误

使用spark sql 处理数据时报这个错误

Exception in thread "main" java.sql.SQLException: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3107 in stage 308.0 failed 4 times, most recent failure: Lost task 3107.3 in stage 308.0 (TID 620318, XXX): org.apache.spark.SparkException: Kryo serialization failed: Buffer overflow. Available: 1572864, required: 3236381Serialization trace:values (org.apache.spark.sql.catalyst.expressions.GenericInternalRow). To avoid this, increase spark.kryoserializer.buffer.max value.        at org.apache.spark.serializer.KryoSerializerInstance.serialize(KryoSerializer.scala:299)        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:240)        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)        at java.lang.Thread.run(Thread.java:745)Driver stacktrace:        at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:275)        at org.apache.hive.jdbc.HiveStatement.executeQuery(HiveStatement.java:355)        at com.peopleyuqing.tool.SparkJDBC.excuteQuery(SparkJDBC.java:64)        at com.peopleyuqing.main.ContentSubThree.main(ContentSubThree.java:24)

方法

val sparkConf = newSparkConf().setAppName(Constants.SPARK_NAME_APP)     .set("spark.kryoserializer.buffer.max","128m");

原因

原因分析： RDD extends scala.AnyRef withscala.Serializable  ，所以在使用textFile ，读取表的数据等大量创建新的rdd,df,ds等 数据集的时候，注意把 这个值调大