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Posted to issues@spark.apache.org by "JinxinTang (Jira)" <ji...@apache.org> on 2020/07/06 00:41:00 UTC
[jira] [Comment Edited] (SPARK-32176) Automatic type promotion to
ArrayType in defined schema in from_json is broken
[ https://issues.apache.org/jira/browse/SPARK-32176?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17151682#comment-17151682 ]
JinxinTang edited comment on SPARK-32176 at 7/6/20, 12:40 AM:
--------------------------------------------------------------
cc [~abhi92544]
Seems can not reproduce：
[[https://www.apache.org/dyn/closer.lua/spark/spark-3.0.0/spark-3.0.0-bin-hadoop2.7.tgz]]
from pyspark.sql.functions import *
from pyspark.sql.types import *
df=spark.read.text("file:/tmp/json/*.json").toDF("stats")
stats_def = StructType().add("hour",IntegerType(),True).add("hits",IntegerType(),True)
df2 = df.select(col("stats"),from_json(col("stats"),ArrayType(stats_def)).alias("stats_array"))
df2.show(5,False)
df2.printSchema
`[file:/tmp/json/a.json|file:///tmp/json/a.json]` data:
[\{"hour":3,"hits":1},\{"hour":4,"hits":1}]
{"hits":20}
was (Author: jinxintang):
cc [~abhi92544]
Seems can not reproduce：
[[https://www.apache.org/dyn/closer.lua/spark/spark-3.0.0/spark-3.0.0-bin-hadoop2.7.tgz]]
from pyspark.sql.functions import *
from pyspark.sql.types import *
df=spark.read.text("file:/tmp/json/*.json").toDF("stats")
stats_def = StructType().add("hour",IntegerType(),True).add("hits",IntegerType(),True)
df2 = df.select(col("stats"),from_json(col("stats"),ArrayType(stats_def)).alias("stats_array"))
df2.show(5,False)
df2.printSchema
`[file:/tmp/json/a.json|file:///tmp/json/a.json]` data:
[\{"hour":3,"hits":1},\{"hour":4,"hits":1}]
{"hits":20}
> Automatic type promotion to ArrayType in defined schema in from_json is broken
> ------------------------------------------------------------------------------
>
> Key: SPARK-32176
> URL: https://issues.apache.org/jira/browse/SPARK-32176
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.0.0
> Reporter: Abhishek Adhikari
> Priority: Major
>
>
> In spark 2.4, I'm able to read data where I have data in mixed types, by defining col "stats" as StringType and later parse the inner data
>
> stats_def = StructType().add("hour",IntegerType(),True).add("hits",IntegerType(),True)
> df2 = df.select(f.col("stats"),f.from_json(f.col("stats"),ArrayType(stats_def)).alias("stats_array"))
> df2.show(5,False)
> df2.printSchema
>
> ||stats||stats_array||
> |[\{"hour":3,"hits":1},\{"hour":4,"hits":1}]|[[3, 1], [4, 1]]|
> |{"hits":20}|[[, 20]]|
> <bound method DataFrame.printSchema of DataFrame[*stats: string, stats_array: array<struct<hour:int,hits:int>>*]>
>
> In spark 3.0.0 it throws error -
> java.lang.ClassCastException: java.lang.Integer cannot be cast to org.apache.spark.sql.catalyst.util.ArrayData
>
> I think it was an important feature and should be supported, maybe with the help of from_json options.
>
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