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From "Ladislav Jech (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (HADOOP-16360) S3A NullPointerException: null uri host. This can be caused by unencoded / in the password string
Date Tue, 11 Jun 2019 12:19:00 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-16360?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Ladislav Jech resolved HADOOP-16360.
------------------------------------
    Resolution: Won't Fix

The bucket name used underscores in name, I replaced with dash and it works.

> S3A NullPointerException: null uri host. This can be caused by unencoded / in the password
string
> -------------------------------------------------------------------------------------------------
>
>                 Key: HADOOP-16360
>                 URL: https://issues.apache.org/jira/browse/HADOOP-16360
>             Project: Hadoop Common
>          Issue Type: Sub-task
>          Components: fs/s3
>    Affects Versions: 3.0.3
>            Reporter: Ladislav Jech
>            Priority: Minor
>
> I am experiencing very old issue appearing now again on Cloudera cluster 6.2. I use following
libraries with pyspark job:
>  * /opt/cloudera/parcels/CDH-6.2.0-1.cdh6.2.0.p0.967373/lib/hadoop/hadoop-common-3.0.0-cdh6.2.0.jar
>  * /opt/cloudera/parcels/CDH-6.2.0-1.cdh6.2.0.p0.967373/lib/hadoop/hadoop-aws-3.0.0-cdh6.2.0.jar
> While trying to write DF to S3 as CSV I get following error:
> {code:java}
> java.lang.NullPointerException: null uri host. This can be caused by unencoded / in the
password string
> 	at java.util.Objects.requireNonNull(Objects.java:228)
> 	at org.apache.hadoop.fs.s3native.S3xLoginHelper.buildFSURI(S3xLoginHelper.java:69)
> 	at org.apache.hadoop.fs.s3a.S3AFileSystem.setUri(S3AFileSystem.java:467)
> 	at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:234)
> 	at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3288)
> 	at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:123)
> 	at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3337)
> 	at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3305)
> 	at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:476)
> 	at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361)
> 	at org.apache.spark.sql.execution.datasources.DataSource.planForWritingFileFormat(DataSource.scala:423)
> 	at org.apache.spark.sql.execution.datasources.DataSource.planForWriting(DataSource.scala:523)
> 	at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:281)
> 	at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:270)
> 	at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:228)
> 	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)
> // code placeholder
> {code}
> I specify secret key via configuration, not via path (as older bugs reported) and on
top of that my Secret key doesn't have any slash, but access key has dash '-' character and 
> AWS_HOST_BASE I define with '[http://host.domain.suffix/'] form
> My code doesn't use secret key in s3 path, but as follows:
> {code:java}
> sparkSession = SparkSession.builder.getOrCreate() 
> sparkContext = sparkSession.sparkContext 
> #sparkContext._jsc.hadoopConfiguration().set("fs.s3a.multipart.size", "1000000") 
> sparkContext._jsc.hadoopConfiguration().set("fs.s3a.access.key", AWS_ACCESS_KEY_ID) sparkContext._jsc.hadoopConfiguration().set("fs.s3a.secret.key",
AWS_SECRET_ACCESS_KEY) sparkContext._jsc.hadoopConfiguration().set("fs.s3a.endpoint", AWS_HOST_BASE)
sparkContext._jsc.hadoopConfiguration().set("fs.s3.access.key", AWS_ACCESS_KEY_ID) sparkContext._jsc.hadoopConfiguration().set("fs.s3.secret.key",
AWS_SECRET_ACCESS_KEY) sparkContext._jsc.hadoopConfiguration().set("fs.s3.endpoint", AWS_HOST_BASE)
sparkContext._jsc.hadoopConfiguration().set("fs.s3n.access.key", AWS_ACCESS_KEY_ID) sparkContext._jsc.hadoopConfiguration().set("fs.s3n.secret.key",
AWS_SECRET_ACCESS_KEY) sparkContext._jsc.hadoopConfiguration().set("fs.s3n.endpoint", AWS_HOST_BASE)

> sqlContext = SQLContext(sparkSession.sparkContext) 
> # log4j = sparkContext._jvm.org.apache.log4j 
> # pylint: disable=W0212
>  logger = sparkContext._jvm.org.apache.log4j.LogManager.getLogger("OracleToS3") 
> # logger = log4j.LogManager.getlogger(__name__) 
> sparkContext.setLogLevel('INFO') 
> logger.info("Going to process Oracle tables...") 
> for table in Source.table_list:
>     logger.info("Reading oracle table into dataframe")
>     oracle_table = sparkContext.read \
>         .format("jdbc") \
>         .option("url", Source.jdbc_string) \
>         .option("dbtable", table) \
>         .option("user", Source.user) \
>         .option("password", Source.password) \
>         .option("driver", "oracle.jdbc.driver.OracleDriver") \
>         .load()
>     # Display schema
>     logger.info("Display table schema")
>     oracle_table.show()
>     logger.info("Display table top 5")
>     oracle_table.head(5)
>     output_file = "s3a://201906/" + "11/" + table + "_" + time.strftime("%Y%m%d_%H%M%S")
+".csv"
>     logger.info("Writing table into S3 to file: " + output_file)
>     oracle_table\
>         .repartition(1)\
>         .write \
>         .mode("overwrite")\
>         .format("csv")\
>         .option("header","true") \
>         .save("s3a://201906/" + "11/" + table + "_" + time.strftime("%Y%m%d_%H%M%S")
+".csv")
> {code}



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