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select JSON_EXTRACT_PATH_TEXT(mod_metadata, 'QCN') as QCN from admin. To query the map columns (converted into json string) you can use JSON_EXTRACT_PATH_TEXT function in Redshift database. Amazon Redshift is a petabyte-scale Cloud-based Data Warehouse service. With this change the Glue job execution was successful and the data was loaded into Amazon Redshift. withColumn("mod_metadata", F.to_json(df1.mod_metadata)) withColumn("rel_metadata", F.to_json(df1.rel_metadata)) ("Convert the map datatype to json datatype") The way I handled this issue is using the “ to_json” pyspark function which converts the map column into JSON string. And as CSV does not support map data type the Glue job was failing. Then these CSV files are loaded into the redshift database via COPY command using the manifest file. Now, the way AWS Glue service internally handles the write_dynamic_frame_from_jdbc_conf method for redshift is to write the Glue DyanamicFrame data into multiple CSV files and create a manifest file onto the S3 location specified in the temporary directory parameter of the Glue job. To debug the issue, if you look at the schema of the data, you will notice that the columns rel_metadata and mod_metadata are map datatype. The AWS Glue job was failing with ‘CSV data source does not support map data type.’ error during the last step of writing the dynamicframe to database. datasink = glueContext.write_dynamic_frame_from_jdbc_conf( The final step in the script was to convert the spark dataframe into Glue DynamicFrame and write it to Amazon Redshift database using write_dynamic_frame_from_jdbc_conf method of glueContext class. withColumn('last_updated', F.from_unixtime(F.col('last_updated')/1000).cast(T.TimestampType()))Ĥ. withColumn('created_at', F.from_unixtime(F.col('created_at')/1000).cast(T.TimestampType())) For example, the last_updated and created_at column with long datatype were converted to timestamp datatype. As part of the script I was performing some basic transformations. The pyspark script started with reading the data from source S3 into a Glue DynamicFrameĭatasource0 = glueContext.create_dynamic_frame_from_options(ģ.13,889 Views 1 Kudo Post Reply Take a Tour of the. One way if you prefer to use string instead of double for that data attribute, you can recreate the parquet file with the column type of string. Lets look into it in little more details – Hello The table column type must match the columnar file format of the Parquet file, else you will result in - 317524. Write the transformed data to Amazon Redshift using write_dynamic_frame_from_jdbc_confĪnd it was during this write step that the glue job was failing.Read the data from S3 using create_dynamic_frame_from_options.In a nutshell, the job was performing below steps: Recently I came across “CSV data source does not support map data type” error for a newly created glue job. AWS Glue is a serverless ETL service to process large amount of datasets from various sources for analytics and data processing. Inspired by Arianas seductively sweet, fun and sexy personality, unlock your most delightful daydream, flirt with the delicious possibilities and find yourself tickled pink with temptation. 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On Tuesday, Ariana Grande finished up her first season as a coach on NBC's The Voice in full fashion form wearing a neon-yellow strapless ball gown from Valentino's acclaimed S/S 19 couture collection. In Jimmy Fallon’s new show That’s My Jam, which premiered November 29 on Peacock, celebrity guests are asked to take part in a series of fun musical-themed games inspired by the most popular Tonight. Now that's how you dress for a grand finale. The Voice star Ariana Grande might forever think twice about being on a team with Blake Shelton after one particularly hilarious incident. |
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