Since df1 and df2 are different DataFrames, you will need to use a join. For 
example: df1.join(df2.selectExpr(“Name”, “NumReads as ctrl_2”), on=[“Name”])

> On Dec 17, 2021, at 16:25, Andrew Davidson <aedav...@ucsc.edu.invalid> wrote:
> 
> 
> Hi I am a newbie
>  
> I have 16,000 data files, all files have the same number of rows and columns. 
> The row ids are identical and are in the same order. I want to create a new 
> data frame that contains the 3rd column from each data file
>  
> I wrote a test program that uses a for loop and Join. It works with my small 
> test set. I get an OOM when I try to run using the all the data files. I 
> realize that join ( map reduce) is probably not a great solution for my 
> problem
>  
> Recently I found several articles that take about the challenge with using 
> withColumn() and talk about how to use select() to append columns
>  
> https://mungingdata.com/pyspark/select-add-columns-withcolumn/
> https://stackoverflow.com/questions/64627112/adding-multiple-columns-in-pyspark-dataframe-using-a-loop
>  
> I am using pyspark spark-3.1.2-bin-hadoop3.2
>  
> I wrote a little test program. It am able to append columns created using 
> pyspark.sql.function.lit(). I am not able to append columns from other data 
> frames
>  
> df1
> DataFrame[Name: string, ctrl_1: double]
> +-------+------+
> |   Name|ctrl_1|
> +-------+------+
> | txId_1|   0.0|
> | txId_2|  11.0|
> | txId_3|  12.0|
> | txId_4|  13.0|
> | txId_5|  14.0|
> | txId_6|  15.0|
> | txId_7|  16.0|
> | txId_8|  17.0|
> | txId_9|  18.0|
> |txId_10|  19.0|
> +-------+------+
>  
> # use select to append multiple literals
> allDF3 = df1.select( ["*", pyf.lit("abc").alias("x"), 
> pyf.lit("mn0").alias("y")] )
>  
> allDF3
> DataFrame[Name: string, ctrl_1: double, x: string, y: string]
> +-------+------+---+---+
> |   Name|ctrl_1|  x|  y|
> +-------+------+---+---+
> | txId_1|   0.0|abc|mn0|
> | txId_2|  11.0|abc|mn0|
> | txId_3|  12.0|abc|mn0|
> | txId_4|  13.0|abc|mn0|
> | txId_5|  14.0|abc|mn0|
> | txId_6|  15.0|abc|mn0|
> | txId_7|  16.0|abc|mn0|
> | txId_8|  17.0|abc|mn0|
> | txId_9|  18.0|abc|mn0|
> |txId_10|  19.0|abc|mn0|
> +-------+------+---+---+
>  
> df2
> DataFrame[Name: string, Length: int, EffectiveLength: double, TPM: double, 
> NumReads: double]
> +-------+------+---------------+----+--------+
> |   Name|Length|EffectiveLength| TPM|NumReads|
> +-------+------+---------------+----+--------+
> | txId_1|  1500|         1234.5|12.1|     0.1|
> | txId_2|  1510|         1244.5|13.1|    11.1|
> | txId_3|  1520|         1254.5|14.1|    12.1|
> | txId_4|  1530|         1264.5|15.1|    13.1|
> | txId_5|  1540|         1274.5|16.1|    14.1|
> | txId_6|  1550|         1284.5|17.1|    15.1|
> | txId_7|  1560|         1294.5|18.1|    16.1|
> | txId_8|  1570|         1304.5|19.1|    17.1|
> | txId_9|  1580|         1314.5|20.1|    18.1|
> |txId_10|  1590|         1324.5|21.1|    19.1|
> +-------+------+---------------+----+--------+
>  
> s2Col = df2["NumReads"].alias( 'ctrl_2' )
> print("type(s2Col) = {}".format(type(s2Col)) )
>  
> type(s2Col) = <class 'pyspark.sql.column.Column'>
>  
> allDF4 = df1.select( ["*", s2Col] )
> ~/extraCellularRNA/sparkBin/spark-3.1.2-bin-hadoop3.2/python/pyspark/sql/dataframe.py
>  in select(self, *cols)
>    1667         [Row(name='Alice', age=12), Row(name='Bob', age=15)]
>    1668         """
> -> 1669         jdf = self._jdf.select(self._jcols(*cols))
>    1670         return DataFrame(jdf, self.sql_ctx)
>    1671 
>  
> ../../sparkBin/spark-3.1.2-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py
>  in __call__(self, *args)
>    1303         answer = self.gateway_client.send_command(command)
>    1304         return_value = get_return_value(
> -> 1305             answer, self.gateway_client, self.target_id, self.name)
>    1306 
>    1307         for temp_arg in temp_args:
>  
> ~/extraCellularRNA/sparkBin/spark-3.1.2-bin-hadoop3.2/python/pyspark/sql/utils.py
>  in deco(*a, **kw)
>     115                 # Hide where the exception came from that shows a 
> non-Pythonic
>     116                 # JVM exception message.
> --> 117                 raise converted from None
>     118             else:
>     119                 raise
>  
> AnalysisException: Resolved attribute(s) NumReads#14 missing from 
> Name#0,ctrl_1#2447 in operator !Project [Name#0, ctrl_1#2447, NumReads#14 AS 
> ctrl_2#2550].;
> !Project [Name#0, ctrl_1#2447, NumReads#14 AS ctrl_2#2550]
> +- Project [Name#0, NumReads#4 AS ctrl_1#2447]
>    +- Project [Name#0, NumReads#4]
>       +- Relation[Name#0,Length#1,EffectiveLength#2,TPM#3,NumReads#4] csv
>  
> Any idea what my bug is?
>  
> Kind regards
>  
> Andy

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