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https://issues.apache.org/jira/browse/SPARK-20528?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16716907#comment-16716907
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vishal kumar yadav commented on SPARK-20528:
--------------------------------------------
Tried this approach also:
import org.apache.spark.sql.functions.udf
val ttoString = udf((payload: Array[Byte]) => new String(payload))
binaryFilesDF.withColumn("_2", ttoString(binaryFilesDF("_2")))
output:
+--------------------+----------------+
| _1| _2|
+--------------------+----------------+
|file:/home/vishal...|
1vd"a(|
+--------------------+----------------+
Concerned : _2, the main content is still in binary format and non-readable
> Add BinaryFileReader and Writer for DataFrames
> ----------------------------------------------
>
> Key: SPARK-20528
> URL: https://issues.apache.org/jira/browse/SPARK-20528
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Joseph K. Bradley
> Priority: Major
> Attachments:
> part-00000-5ae00646-8400-4b45-aa6f-d6f27068972c-c000.json, stocklist.json,
> stocklist.pdub
>
>
> It would be very useful to have a binary data reader/writer for DataFrames,
> presumably called via {{spark.read.binaryFiles}}, etc.
> Currently, going through RDDs is annoying since it requires different code
> paths for Scala vs Python:
> Scala:
> {code}
> val binaryFilesRDD = sc.binaryFiles("mypath")
> val binaryFilesDF = spark.createDataFrame(binaryFilesRDD)
> {code}
> Python:
> {code}
> binaryFilesRDD = sc.binaryFiles("mypath")
> binaryFilesRDD_recast = binaryFilesRDD.map(lambda x: (x[0], bytearray(x[1])))
> binaryFilesDF = spark.createDataFrame(binaryFilesRDD_recast)
> {code}
> This is because Scala and Python {{sc.binaryFiles}} return different types,
> which makes sense in RDD land but not DataFrame land.
> My motivation here is working with images in Spark.
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