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https://issues.apache.org/jira/browse/SPARK-34751?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17303001#comment-17303001
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Nivas Umapathy edited comment on SPARK-34751 at 3/17/21, 12:52 AM:
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the schema is extracted from the same file, before materializing the data
{{{{df =
glue_context.read.schema(df.schema).parquet(}}{{'invalid_columns_double.parquet')}}}}
{{{{ ^^^^^^^^^^^^^^^^^}}}}
by schema I meant this. The file was written out from pandas dataframe.
It was written out using this
{{}}
{{import pandas as pd}}
{{df = pd.DataFrame(}}
{{data = {}}
{{"COL 1":
[87.0921538,41.26487033,1.731626487,99.02779887,80.750347,62.89799664,84.27772144,12.78995399,58.13994625,54.51677768],}}
{{"COL,2":
[28.431596,13.50141322,28.60878912,50.59429628,53.77345338,3.278319754,89.88524435,57.29173215,34.75955608,22.50907852],}}
{{"COL;3":
[48.12359525,2.751809433,64.45305108,40.97279762,46.3506431,68.57561523,67.52866381,18.70752371,44.86086801,8.42884315],}}
{{"COL{4":
[25.23141131,65.20640894,56.83503264,21.46097087,59.22963758,99.55784318,8.02616508,75.29924438,3.911268106,90.1820556],}}
{{"COL}5":
[37.00662369,82.24478025,27.89576774,9.549598639,46.92239754,10.48954042,81.71312268,49.991685,43.78556399,79.00133828],}}
{{"COL(6":
[71.21354798,82.33860851,12.88393027,23.47301417,76.36836392,18.43024893,51.48770487,93.20889954,72.66516434,18.07311939],}}
{{"COL)7":
[68.00032082,39.91265109,83.47701751,42.71072597,33.54784094,94.63751895,3.364241739,0.792257736,78.63395232,70.8626348],}}
{{"COL\n8":
[77.80604836,61.08923308,70.70871195,99.33277829,79.77837072,56.28812485,34.03977847,13.40720489,87.71281052,64.80060217],}}
{{"COL=9":
[60.00505851,46.51367893,87.1346726,7.202332939,49.50378799,56.70949031,99.39792697,52.08074715,18.25891755,67.88110289],}}
{{"COL\t10":
[78.60259718,96.87558507,20.04134901,80.46408956,69.97610739,42.96954652,22.45733464,32.00411095,52.83023296,87.48870904],}}
{{}, columns = ["COL
1","COL,2","COL;3","COL\{4","COL}5","COL(6","COL)7","COL\n8","COL=9","COL\t10"])}}
{{df.to_parquet('invalid_columns_double.parquet')}}
Here is a link to my databricks notebook
[https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/5940072345564347/3863439224328194/623184285031795/latest.html]
was (Author: toocoolblue2000):
the schema is extracted from the same file, before materializing the data
{{{{df =
glue_context.read.schema(df.schema).parquet(}}{{'invalid_columns_double.parquet')}}}}
{{{{ ^^^^^^^^^^^^^^^^^}}}}
by schema I meant this. The file was written out from pandas dataframe.
Here is a link to my databricks notebook
https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/5940072345564347/3863439224328194/623184285031795/latest.html
> Parquet with invalid chars on column name reads double as null when a clean
> schema is applied
> ---------------------------------------------------------------------------------------------
>
> Key: SPARK-34751
> URL: https://issues.apache.org/jira/browse/SPARK-34751
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
> Affects Versions: 2.4.3, 3.1.1
> Environment: Pyspark 2.4.3
> AWS Glue Dev Endpoint EMR
> Reporter: Nivas Umapathy
> Priority: Major
> Attachments: invalid_columns_double.parquet
>
>
> I have a parquet file that has data with invalid column names on it.
> [#Reference](https://issues.apache.org/jira/browse/SPARK-27442) Here is the
> file attached with this ticket.
> I tried to load this file with
> {{df = glue_context.read.parquet('invalid_columns_double.parquet')}}
> {{df = df.withColumnRenamed('COL 1', 'COL_1')}}
> {{df = df.withColumnRenamed('COL,2', 'COL_2')}}
> {{df = df.withColumnRenamed('COL;3', 'COL_3') }}
> and so on.
> Now if i call
> {{df.show()}}
> it throws this exception that is still pointing to the old column name.
> {{pyspark.sql.utils.AnalysisException: 'Attribute name "COL 1" contains
> invalid character(s) among " ,;{}()}}
> {{n}}
> {{t=". Please use alias to rename it.;'}}
>
> When i read about it in some blogs, there was suggestion to re-read the same
> parquet with new schema applied. So i did
> {{df =
> glue_context.read.schema(df.schema).parquet(}}{{'invalid_columns_double.parquet')}}
>
> and it works, but all the data in the dataframe are null. The same works for
> String datatypes
>
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