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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