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I'm trying to build gold level streaming live table based on two streaming silver live tables with left join.This attempt fails with the next error:"Append mode error: Stream-stream LeftOuter join between two streaming DataFrame/Datasets is not suppo...
Hi,Assume that I have a streaming delta table. Is there any way to get snapshot of the streaming table as a static table?Reason is that I need to join this streaming table with a static table by:output = output.join(country_information, ["Country"], ...
Whenever I apply a CROSS JOIN to my Databricks SQL query I get a message letting me know that a column does not exists, but I'm not sure if the issue is with the CROSS JOIN.For example, the code should identify characters such as http, https, ://, / ...
@CARLTON PATTERSON Since you have given an alias "tt" to your table "basecrmcbreport.organizations", to access corresponding columns you will have to access them in format tt.<column_name>in your code in line #4, try accessing the column 'homepage_u...
Hello all, I m using pyspark ( python 3.8) over spark3.0 on Databricks. When running this DataFrame join:next_df = days_currencies_matrix.alias('a').join( data_to_merge.alias('b') , [
days_currencies_matrix.dt == data_to_merge.RATE_DATE,
days...
@Alessio Palma - Howdy! My name is Piper, and I'm a moderator for the community. Would you be happy to mark whichever answer solved your issue so other members may find the solution more quickly?
I would like to keep only one of the columns used to join the dataframes. Using select() after the join does not seem straight forward because the real data may have many columns or the column names may not be known. A simple example belowllist = [(...
This is an expected behavior. DataFrame.join method is equivalent to SQL join like thisSELECT*FROM a JOIN b ON joinExprsIf you want to ignore duplicate columns just drop them or select columns of interest afterwards. If you want to disambiguate you c...
Sometimes the error is part of
"org.apache.spark.SparkException: Exception thrown in awaitResult:".
The error source is the step, where we extract the second time the rows, where the data is updated. We can count the rows, but we cannot display or w...
Thanks Lleido. I eventually found I had changed the schema of a partitioned DataFrame that I had made inadvertently where I narrowed a column's type from a long to an integer. While rather obvious cause of the problem in hindsight it was terribly di...
Analyze is not needed with parquet tables that use the databricks parquet package. That is the default now when you use .saveAsTable(), but if you use a different output format - it's possible that analyze may not work yet.