Sorry, I meant setLong only. If you know which version of hadoop jars
you're using, you can check the code here
<https://github.com/apache/hadoop/blob/trunk/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/S3AFileSystem.java>
to try to find out which line exactly is throwing the error.
~ Hariharan
On Thu, Oct 15, 2020 at 8:56 PM Devi P V <devipvina...@gmail.com> wrote:
> hadoop_conf.set("fs.s3a.multipart.size", 104857600L)
>
> .set only allows string values. Its throwing invalid syntax.
>
> I tried following also. But issue not fixed.
>
> hadoop_conf.setLong("fs.s3a.multipart.size", 104857600)
>
> Thanks
>
>
> On Thu, Oct 15, 2020, 7:22 PM Hariharan <hariharan...@gmail.com> wrote:
>
>> fs.s3a.multipart.size needs to be a long value, not a string, so you
>> will need to use
>>
>> hadoop_conf.set("fs.s3a.multipart.size", 104857600L)
>>
>> ~ Hariharan
>>
>> On Thu, Oct 15, 2020 at 6:32 PM Devi P V <devipvina...@gmail.com> wrote:
>> >
>> > Hi All,
>> >
>> > I am trying to write a pyspark dataframe into KMS encrypted S3 bucket.I
>> am using spark-3.0.1-bin-hadoop3.2. I have given all the possible
>> configurations as shown below.
>> >
>> > sc = spark.sparkContext
>> > hadoop_conf = sc._jsc.hadoopConfiguration()
>> > hadoop_conf.set("fs.s3a.access.key", "XXX")
>> > hadoop_conf.set("fs.s3a.secret.key","XXX")
>> > hadoop_conf.set("fs.s3a.multipart.size", "104857600")
>> > hadoop_conf.set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
>> > hadoop_conf.setBoolean("fs.s3a.sse.enabled",True)
>> > hadoop_conf.set("fs.s3a.server-side-encryption-algorithm", "SSE-KMS")
>> > hadoop_conf.set("fs.s3a.sse.kms.keyId", "XXXX")
>> >
>> >
>> >
>> > df = spark.createDataFrame(
>> > [
>> > (1, 'one'),
>> > (2, 'two'),
>> > ],
>> > ['id', 'txt']
>> > )
>> > df.write.csv('s3a://bucket_name/test_data',header='true')
>> >
>> > Getting exception
>> >
>> > : java.lang.IllegalArgumentException
>> > at
>> java.util.concurrent.ThreadPoolExecutor.<init>(ThreadPoolExecutor.java:1314)
>> > at
>> java.util.concurrent.ThreadPoolExecutor.<init>(ThreadPoolExecutor.java:1237)
>> > at
>> org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:274)
>> > at
>> org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3303)
>> > at
>> org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124)
>> > at
>> org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3352)
>> > at
>> org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3320)
>> > at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:479)
>> > at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361)
>> > at
>> org.apache.spark.sql.execution.datasources.DataSource.planForWritingFileFormat(DataSource.scala:459)
>> > at
>> org.apache.spark.sql.execution.datasources.DataSource.planForWriting(DataSource.scala:559)
>> > at
>> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:415)
>> > at
>> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:399)
>> > at
>> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:288)
>> > at
>> org.apache.spark.sql.DataFrameWriter.csv(DataFrameWriter.scala:953)
>> > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>> > at
>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>> > at
>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>> > at java.lang.reflect.Method.invoke(Method.java:498)
>> > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
>> > at
>> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
>> > at py4j.Gateway.invoke(Gateway.java:282)
>> > at
>> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
>> > at py4j.commands.CallCommand.execute(CallCommand.java:79)
>> > at py4j.GatewayConnection.run(GatewayConnection.java:238)
>> > at java.lang.Thread.run(Thread.java:748)
>> >
>> > Any idea to resolve this issue ?
>> >
>> > Thanks
>>
>
