Convert pyspark dataframe to pandas dataframe

Question

I have pyspark dataframe where its dimension is (28002528,21) and tried to convert it to pandas dataframe by using the following code line :

pd_df=spark_df.toPandas()

I got this error:

first Part

Py4JJavaError: An error occurred while calling o170.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 39.0 failed 1 times, most recent failure: Lost task 3.0 in stage 39.0 (TID 89, localhost, executor driver): java.lang.OutOfMemoryError: Java heap space
    at java.util.Arrays.copyOf(Arrays.java:3236)
    at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
    at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
    at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
    at net.jpountz.lz4.LZ4BlockOutputStream.flushBufferedData(LZ4BlockOutputStream.java:220)
    at net.jpountz.lz4.LZ4BlockOutputStream.write(LZ4BlockOutputStream.java:173)
    at java.io.DataOutputStream.write(DataOutputStream.java:107)
    at org.apache.spark.sql.catalyst.expressions.UnsafeRow.writeToStream(UnsafeRow.java:552)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:256)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)


Driver stacktrace:
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)
        ...
        ...

Caused by: java.lang.OutOfMemoryError: Java heap space
        ...
        ...

Second Part

Exception happened during processing of request from ('127.0.0.1', 56842)
ERROR:py4j.java_gateway:An error occurred while trying to connect to the Java server (127.0.0.1:56657)
Traceback (most recent call last):
        ...
        ...    
ConnectionResetError: [WinError 10054] An existing connection was forcibly closed by the remote host

During handling of the above exception, another exception occurred:
        ...
        ...

and I tried also to take sample of the original pyspark dataframe

smaple_pd_df=spark_df.sample(0.05).toPandas()

I got an error looks like the first part only of the previous error

ulmefors ulmefors · Accepted Answer · 2019-02-25T13:15:24

You get java.lang.OutOfMemoryError which probably means that you are trying to load all data into a single node which doesn't have enough RAM to handle the entire DataFrame. If you are using a cloud solution provider such as Databricks, try increasing the size of cluster RAM.

Convert pyspark dataframe to pandas dataframe

2 Answers