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Reg:- Py4JError in Windows 10 with Spark

Hi , I am getting error :- --- Py4JError Traceback (most recent call last) in () 3 TOTAL = 100 4 dots = sc.parallelize([2.0 * np.random.random(2) - 1.0 for i in range( TOTAL)]).cache() > 5 print("Number of random

Any good book recommendations for SparkR

Hi Team, Any good book recommendations for get in-depth knowledge from zero to production. Let me know. Thanks.

Issue with map function in Spark 2.2.0

utor.scala:345) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) ... 1 more Please help me in this . Thanks. Nandan Priyadarshi

Not able to access Pyspark into Jupyter notebook

Hi Users, Currently, I am trying to use Apache Spark 2.2.0 by using a Jupyter notebook but not able to achieve it. I am using Ubuntu 17.10. I can able to use pyspark in command line as well as spark-shell . Please give some ideas. Thanks. Nandan Priyadarshi

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Spark Xml schema help

ucture??? Thanks and Regards, Nandan

Union of multiple RDDs

Hello, I am trying to combine several small text files (each file is approx hundreds of MBs to 2-3 gigs) into one big parquet file. I am loading each one of them and trying to take a union, however this leads to enormous amounts of partitions, as union keeps on adding the partitions of the input

RDD generated from Dataframes

Hello everyone, Generally speaking, I guess it's well known that dataframes are much faster than RDD when it comes to performance. My question is how do you go around when it comes to transforming a dataframe using map. I mean then the dataframe gets converted into RDD, hence now do you again

Continuous WARN messages from BlockManager about block replication

? thanks Nandan