Unable write data using spark submit

Question

when I'm doing spark-submit using this command on Cloudera

**time spark-submit \
--deploy-mode client \
--conf spark.app.name='XXXxxxxxx' 
--conf spark.master=local[*] \
--conf spark.driver.memory=20g \
--conf spark.driver.cores=2 \
--conf spark.executor.instances=4 \
--conf spark.executor.memory=20g \
--conf spark.executor.cores=7 \
--conf spark.dynamicAllocation.enabled=True \
--conf spark.dynamicAllocation.minExecutors=0 \
--conf spark.dynamicAllocation.maxExecutors=5 \
--conf spark.dynamicAllocation.executorAllocationRatio=0.5 \
--conf spark.local.dir=/data/xxx/ssss/spark_local/ \
--py-files test.py \
--files test_ed.ini \
test_py.py**

I am getting this in my output log file:

**Caused by: java.io.FileNotFoundException: /xxx/xxxxx/xxx/xxx/spark_local (Too many open files)
    at java.io.FileOutputStream.open0(Native Method)
    at java.io.FileOutputStream.open(FileOutputStream.java:270)
    at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
    at org.apache.spark.storage.DiskBlockObjectWriter.initialize(DiskBlockObjectWriter.scala:105)
    at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:118)
    at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:245)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:158)
    at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
    at org.apache.spark.scheduler.Task.run(Task.scala:131)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more**

I have tried the shuffle partition after this job gets successful, but my downstream job also fails after that.