I have pyspark dataframe with a column named Filters: “array>”
I want to save my dataframe in csv file, for that i need to cast the array to string type.
I tried to cast it: DF.Filters.tostring()
and DF.Filters.cast(StringType())
, but both solutions generate error message for each row in the columns Filters:
org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@56234c19
The code is as follows
from pyspark.sql.types import StringType DF.printSchema() |-- ClientNum: string (nullable = true) |-- Filters: array (nullable = true) |-- element: struct (containsNull = true) |-- Op: string (nullable = true) |-- Type: string (nullable = true) |-- Val: string (nullable = true) DF_cast = DF.select ('ClientNum',DF.Filters.cast(StringType())) DF_cast.printSchema() |-- ClientNum: string (nullable = true) |-- Filters: string (nullable = true) DF_cast.show() | ClientNum | Filters | 32103 | org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@d9e517ce | 218056 | org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3c744494
Sample JSON data:
{"ClientNum":"abc123","Filters":[{"Op":"foo","Type":"bar","Val":"baz"}]}
Thanks !!
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Answer
I created a sample JSON dataset to match that schema:
{"ClientNum":"abc123","Filters":[{"Op":"foo","Type":"bar","Val":"baz"}]} select(s.col("ClientNum"),s.col("Filters").cast(StringType)).show(false) +---------+------------------------------------------------------------------+ |ClientNum|Filters | +---------+------------------------------------------------------------------+ |abc123 |org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@60fca57e| +---------+------------------------------------------------------------------+
Your problem is best solved using the explode() function which flattens an array, then the star expand notation:
s.selectExpr("explode(Filters) AS structCol").selectExpr("structCol.*").show() +---+----+---+ | Op|Type|Val| +---+----+---+ |foo| bar|baz| +---+----+---+
To make it a single column string separated by commas:
s.selectExpr("explode(Filters) AS structCol").select(F.expr("concat_ws(',', structCol.*)").alias("single_col")).show() +-----------+ | single_col| +-----------+ |foo,bar,baz| +-----------+
Explode Array reference: Flattening Rows in Spark
Star expand reference for “struct” type: How to flatten a struct in a spark dataframe?