我正在运行Spark 2并试图改变大约5 TB的json。在Dataset改组时，我遇到了很长时间的垃圾收集暂停：
val operations = spark.read.json(inPath).as[MyClass]
operations.repartition(partitions, operations("id")).write.parquet("s3a://foo")
是否有任何明显的配置调整来处理这个问题？我的配置如下：
spark.driver.maxResultSize 6G
spark.driver.memory 10G
spark.executor.extraJavaOptions -XX:+UseG1GC -XX:MaxPermSize=1G -XX:+HeapDumpOnOutOfMemoryError
spark.executor.memory 32G
spark.hadoop.fs.s3a.buffer.dir /raid0/spark
spark.hadoop.fs.s3n.buffer.dir /raid0/spark
spark.hadoop.fs.s3n.multipart.uploads.enabled true
spark.hadoop.parquet.block.size 2147483648
spark.hadoop.parquet.enable.summary-metadata false
spark.local.dir /raid0/spark
spark.memory.fraction 0.8
spark.mesos.coarse true
spark.mesos.constraints priority:1
spark.mesos.executor.memoryOverhead 16000
spark.network.timeout 600
spark.rpc.message.maxSize 1000
spark.speculation false
spark.sql.parquet.mergeSchema false
spark.sql.planner.externalSort true
spark.submit.deployMode client
spark.task.cpus 1
答案 0 :(得分：5)