Member since
04-05-2016
37
Posts
8
Kudos Received
9
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
2979 | 07-30-2019 11:52 PM | |
5344 | 06-07-2019 01:01 AM | |
9223 | 04-14-2017 08:31 PM | |
5649 | 08-03-2016 12:52 AM | |
2939 | 06-22-2016 02:10 AM |
02-29-2024
10:24 PM
How about submitting a CDE job from CML to a private cloud base cluster?
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07-31-2020
05:54 AM
In a CDH 6.3.2 cluster have an Anaconda parcel distributed and activated, which of course has the numpy module installed. However the Spark nodes seem to ignore the CDH configuration and keep using the system wide Python from /usr/bin/python. Nevertheless I have installed numpy in system wide Python across all cluster nodes. However I still experience the "ImportError: No module named numpy". Would appreciate any further advice how to solve the problem. Not sure how to implement the solution referred in https://stackoverflow.com/questions/46857090/adding-pyspark-python-path-in-oozie.
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02-05-2020
10:12 PM
while i running this programming i got these error can anyone help me with this [cloudera@quickstart ~]$ spark-shell --master yarn-client Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/usr/lib/zookeeper/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/usr/lib/flume-ng/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/usr/lib/parquet/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/usr/lib/avro/avro-tools-1.7.6-cdh5.13.0.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory] Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 1.6.0 /_/ Using Scala version 2.10.5 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_67) Type in expressions to have them evaluated. Type :help for more information. 20/02/05 22:03:26 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 20/02/05 22:03:42 WARN shortcircuit.DomainSocketFactory: The short-circuit local reads feature cannot be used because libhadoop cannot be loaded. Spark context available as sc (master = yarn-client, app id = application_1580968178673_0001). SQL context available as sqlContext.
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07-30-2019
11:52 PM
1 Kudo
Since the "list" commands gets the apps from the ResourceManager and doesn't set any explicit filters and limits (except those provided with it) on the request, technically it returns all the applications which are present with RM at the moment. That number is controlled by "yarn.resourcemanager.max-completed-applications" config. Hope that clarifies.
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06-07-2019
01:01 AM
1 Kudo
As your intent seems to capture the driver logs in a separate file while executing the app in the cluster mode, make sure that '/some/path/to/edgeNode/' dir is present on all of the NodeManager essentially as in cluster mode the driver will be running in the Yarn app's application master. If you can't make sure that follow a general practice to provide log file path to some pre-existing paths e.g. "/var/log/SparkDriver.log".
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09-24-2018
11:19 PM
Hello Experts,
We are upgrading Our Cloudera Hive from 1.3 to 2.0, Could you please let us know, if there is known issues related to this, i did a search in Tableau and Cloudera Community, but i didn't found any issues.
Thanks in Advance!!!
Regards,
Muthu Venkatesh
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07-28-2017
12:20 PM
How do I query hive tables from spark 2.0 . Could you share the steps.
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05-01-2017
11:11 PM
Hi, i am facing the below mentioned issue. Please help me to solve it 17/05/02 11:07:13 ERROR ShutdownHookManager: Exception while deleting Spark temp dir: C:\Users\arpitbh\AppData\Local\Temp\spark-07d9637a-2eb8-4a32-8490-01e106a80d6b java.io.IOException: Failed to delete: C:\Users\arpitbh\AppData\Local\Temp\spark-07d9637a-2eb8-4a32-8490-01e106a80d6b at org.apache.spark.util.Utils$.deleteRecursively(Utils.scala:1010) at org.apache.spark.util.ShutdownHookManager$$anonfun$1$$anonfun$apply$mcV$sp$3.apply(ShutdownHookManager.scala:65) at org.apache.spark.util.ShutdownHookManager$$anonfun$1$$anonfun$apply$mcV$sp$3.apply(ShutdownHookManager.scala:62) at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33) at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186) at org.apache.spark.util.ShutdownHookManager$$anonfun$1.apply$mcV$sp(ShutdownHookManager.scala:62) at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:216) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ShutdownHookManager.scala:188) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188) at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1951) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply$mcV$sp(ShutdownHookManager.scala:188) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188) at scala.util.Try$.apply(Try.scala:192) at org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:188) at org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:178) at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54)
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04-14-2017
08:31 PM
It is the below line which is setting the data types for both the fields as StringType: val schema =
StructType(
schemaString.split(" ").map(fieldName => StructField(fieldName, StringType, true))) You can define your custom schema as follows : val customSchema = StructType(Array(
StructField("name", StringType, true),
StructField("age", IntegerType, true))) You can add additional fields as well in the above schema definition. And then you can use this customSchema while creating the dataframe as follows: val peopleDataFrame = sqlContext.createDataFrame(rowRDD, customSchema) Also for details, please see this page.
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04-05-2017
07:28 PM
1 Kudo
The cause of my case was described in Message 4-5 of the thread. Here are some possible solutions set spark.local.dir to somewhere else outside /tmp . Refer to Spark Configuration for how to configure the value. disable housekeeping of /tmp/spark-... periodic restart your spark streaming job
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