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Posted to issues@spark.apache.org by "Stuart Reynolds (JIRA)" <ji...@apache.org> on 2017/07/12 22:23:00 UTC

[jira] [Updated] (SPARK-21392) Unable to infer schema when loading large Parquet file

     [ https://issues.apache.org/jira/browse/SPARK-21392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Stuart Reynolds updated SPARK-21392:
------------------------------------
    Description: 
The following boring code works

{code:none}
response = "mi_or_chd_5"
sc = get_spark_context() # custom
sqlc = get_sparkSQLContextWithTables(sc, tables=["outcomes"]) # custom


rdd = sqlc.sql("SELECT eid,mi_or_chd_5 FROM outcomes")
print rdd.schema
#>>    StructType(List(StructField(eid,IntegerType,true),StructField(mi_or_chd_5,ShortType,true)))
rdd.show()
#+-------+-----------+
#|    eid|mi_or_chd_5|
#+-------+-----------+
#|216|       null|
#|431|       null|
#|978|          0|
#|852|          0|
#|418|          0|

rdd.write.parquet(response, mode="overwrite") # success!
rdd2 = sqlc.read.parquet(response) # fail
{code}
    
fails with:

{code:none}AnalysisException: u'Unable to infer schema for Parquet. It must be specified manually.;'
{code}

in 

{code:none} /usr/local/lib/python2.7/dist-packages/pyspark-2.1.0+hadoop2.7-py2.7.egg/pyspark/sql/utils.pyc in deco(*a, **kw)
{code}

The documentation for parquet says the format is self describing, and the full schema was available when the parquet file was saved. What gives?

The error doesn't happen if I add "limit 10" to the sql query. The whole selected table is 500k rows with an int and short column.

Seems related to: https://issues.apache.org/jira/browse/SPARK-16975, but which claims it was fixed in 2.0.1, 2.1.0. (Current bug is 2.1.1)


  was:
The following boring code works

{code:none}
    response = "mi_or_chd_5"

    outcome = sqlc.sql("""select eid,{response} as response
        from outcomes
        where {response} IS NOT NULL""".format(response=response))
    outcome.write.parquet(response, mode="overwrite")
    
    >>> print outcome.schema
    StructType(List(StructField(eid,IntegerType,true),StructField(response,ShortType,true)))
{code}
    
But then,
{code:none}
    outcome2 = sqlc.read.parquet(response)  # fail
{code}

fails with:

{code:none}AnalysisException: u'Unable to infer schema for Parquet. It must be specified manually.;'
{code}

in 

{code:none} /usr/local/lib/python2.7/dist-packages/pyspark-2.1.0+hadoop2.7-py2.7.egg/pyspark/sql/utils.pyc in deco(*a, **kw)
{code}

The documentation for parquet says the format is self describing, and the full schema was available when the parquet file was saved. What gives?

Seems related to: https://issues.apache.org/jira/browse/SPARK-16975, but which claims it was fixed in 2.0.1, 2.1.0. (Current bug is 2.1.1)


        Summary: Unable to infer schema when loading large Parquet file  (was: Unable to infer schema when loading Parquet file)

> Unable to infer schema when loading large Parquet file
> ------------------------------------------------------
>
>                 Key: SPARK-21392
>                 URL: https://issues.apache.org/jira/browse/SPARK-21392
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.1.1
>         Environment: Spark 2.1.1. python 2.7.6
>            Reporter: Stuart Reynolds
>              Labels: parquet, pyspark
>
> The following boring code works
> {code:none}
> response = "mi_or_chd_5"
> sc = get_spark_context() # custom
> sqlc = get_sparkSQLContextWithTables(sc, tables=["outcomes"]) # custom
> rdd = sqlc.sql("SELECT eid,mi_or_chd_5 FROM outcomes")
> print rdd.schema
> #>>    StructType(List(StructField(eid,IntegerType,true),StructField(mi_or_chd_5,ShortType,true)))
> rdd.show()
> #+-------+-----------+
> #|    eid|mi_or_chd_5|
> #+-------+-----------+
> #|216|       null|
> #|431|       null|
> #|978|          0|
> #|852|          0|
> #|418|          0|
> rdd.write.parquet(response, mode="overwrite") # success!
> rdd2 = sqlc.read.parquet(response) # fail
> {code}
>     
> fails with:
> {code:none}AnalysisException: u'Unable to infer schema for Parquet. It must be specified manually.;'
> {code}
> in 
> {code:none} /usr/local/lib/python2.7/dist-packages/pyspark-2.1.0+hadoop2.7-py2.7.egg/pyspark/sql/utils.pyc in deco(*a, **kw)
> {code}
> The documentation for parquet says the format is self describing, and the full schema was available when the parquet file was saved. What gives?
> The error doesn't happen if I add "limit 10" to the sql query. The whole selected table is 500k rows with an int and short column.
> Seems related to: https://issues.apache.org/jira/browse/SPARK-16975, but which claims it was fixed in 2.0.1, 2.1.0. (Current bug is 2.1.1)



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