Ladislav Jech created HADOOP-16360:
--------------------------------------

             Summary: java.lang.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: Improvement
            Reporter: Ladislav Jech


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}
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 ADDCSource.table_list: logger.info("Reading oracle 
table into dataframe") oracle_table = sparkContext.read \ .format("jdbc") \ 
.option("url", ADDCSource.jdbc_string) \ .option("dbtable", table) \ 
.option("user", ADDCSource.user) \ .option("password", ADDCSource.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://ADDC_ELICTRICITY_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://ADDC_ELICTRICITY_201906/" + "11/" + table + "_" + 
time.strftime("%Y%m%d_%H%M%S") +".csv")
{code}



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: common-dev-unsubscr...@hadoop.apache.org
For additional commands, e-mail: common-dev-h...@hadoop.apache.org

Reply via email to