老师，我本地跑应用解析文件，最后保存到一个文件时，提示内存不够，该怎么设置呢？

 resultDF.coalesce(1).write.format("com.databricks.spark.csv").save("D://Froad/BigData/output/a.csv")

错误日志

19/06/23 14:22:56 INFO TaskMemoryManager: 0 bytes of memory were used by task 212 but are not associated with specific consumers
19/06/23 14:22:56 INFO TaskMemoryManager: 2084553678 bytes of memory are used for execution and 749413 bytes of memory are used for storage
19/06/23 14:22:56 ERROR Utils: Aborting task
org.apache.spark.memory.SparkOutOfMemoryError: Unable to acquire 52 bytes of memory, got 0
	at org.apache.spark.memory.MemoryConsumer.throwOom(MemoryConsumer.java:157)
	at org.apache.spark.memory.MemoryConsumer.allocatePage(MemoryConsumer.java:119)
	at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.acquireNewPageIfNecessary(UnsafeExternalSorter.java:383)
	at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.insertRecord(UnsafeExternalSorter.java:407)
	at org.apache.spark.sql.execution.UnsafeExternalRowSorter.insertRow(UnsafeExternalRowSorter.java:135)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage8.sort_addToSorter_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage8.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$2.hasNext(WholeStageCodegenExec.scala:636)
	at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83)
	at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.advancedBufferedToRowWithNullFreeJoinKey(SortMergeJoinExec.scala:811)
	at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.<init>(SortMergeJoinExec.scala:686)
	at org.apache.spark.sql.execution.joins.SortMergeJoinExec.$anonfun$doExecute$1(SortMergeJoinExec.scala:220)
	at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.rdd.CoalescedRDD.$anonfun$compute$1(CoalescedRDD.scala:100)
	at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$1(FileFormatWriter.scala:244)
	at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:242)
	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:177)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:121)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:748)