[jira] [Created] (SPARK-5722) Infer_schma_type incorrect for Integers in pyspark

["Don Drake (JIRA)" <ji...@apache.org>]

Don Drake created SPARK-5722:
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             Summary: Infer_schma_type incorrect for Integers in pyspark
                 Key: SPARK-5722
                 URL: https://issues.apache.org/jira/browse/SPARK-5722
             Project: Spark
          Issue Type: Bug
          Components: PySpark
    Affects Versions: 1.2.0
            Reporter: Don Drake



The Integers datatype in Python does not match what a Scala/Java integer is defined as.   This causes inference of data types and schemas to fail when data is larger than 2^32 and it is inferred incorrectly as an Integer.

Since the range of valid Python integers is wider than Java Integers, this causes problems when inferring Integer vs. Long datatypes.  This will cause problems when attempting to save SchemaRDD as Parquet or JSON.

Here's an example:

>>> sqlCtx = SQLContext(sc)
>>> from pyspark.sql import Row
>>> rdd = sc.parallelize([Row(f1='a', f2=100000000000000)])
>>> srdd = sqlCtx.inferSchema(rdd)
>>> srdd.schema()
StructType(List(StructField(f1,StringType,true),StructField(f2,IntegerType,true)))

That number is a LongType in Java, but an Integer in python.  We need to check the value to see if it should really by a LongType when a IntegerType is initially inferred.

More tests:
>>> from pyspark.sql import _infer_type
# OK
>>> print _infer_type(1)
IntegerType
# OK
>>> print _infer_type(2**31-1)
IntegerType
#WRONG
>>> print _infer_type(2**31)
#WRONG
IntegerType
>>> print _infer_type(2**61 )
#OK
IntegerType
>>> print _infer_type(2**71 )
LongType

Java Primitive Types defined:
http://docs.oracle.com/javase/tutorial/java/nutsandbolts/datatypes.html

Python Built-in Types:
https://docs.python.org/2/library/stdtypes.html#typesnumeric




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