[jira] [Created] (SPARK-29830) PySpark.context.Sparkcontext.binaryfiles improved memory with buffer

["Jörn Franke (Jira)" <ji...@apache.org>]

Jörn Franke created SPARK-29830:
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             Summary: PySpark.context.Sparkcontext.binaryfiles improved memory with buffer
                 Key: SPARK-29830
                 URL: https://issues.apache.org/jira/browse/SPARK-29830
             Project: Spark
          Issue Type: Improvement
          Components: PySpark
    Affects Versions: 2.4.4
            Reporter: Jörn Franke


At the moment, Pyspark reads binary files into a byte array directly. This means it reads the full binary file immediately into memory, which is 1) memory in-efficient 2) differs from the Scala implementation (see pyspark here: [https://spark.apache.org/docs/2.4.0/api/python/_modules/pyspark/context.html#SparkContext.binaryFiles).   |https://spark.apache.org/docs/2.4.0/api/python/_modules/pyspark/context.html#SparkContext.binaryFiles]

In Scala, Spark returns a PortableDataStream, which means the application does not need to read the full content of the stream in memory to work on it (see [https://spark.apache.org/docs/2.4.0/api/scala/index.html#org.apache.spark.SparkContext).]

 

Hence, it is proposed to adapt the Pyspark implementation to return something similar to a PortableDataStream in Scala (e.g. [BytesIO|[https://docs.python.org/3/library/io.html#io.BytesIO].]

 

Reading binary files in an efficient manner is crucial for many IoT applications, but potentially also other fields (e.g. disk image analysis in forensics).



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