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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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