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selecting multiple rows with a list of id pyspark



2019 Community Moderator ElectionCreating multiple pyspark dataframes from a single dataframeHow do I check if a list is empty?Finding the index of an item given a list containing it in PythonDifference between append vs. extend list methods in PythonHow to randomly select an item from a list?How to make a flat list out of list of lists?How to concatenate two lists in Python?How to clone or copy a list?How do I list all files of a directory?How to read a file line-by-line into a list?Catch multiple exceptions in one line (except block)










0















I have a table in spark, which has ID and numOfReq attributes.
in ID, it is between 1 to 100 and it's not in order, and each ID can be repeated many times in the table. I want to extract rows with 1, 47, 54 and 89 IDs. I can do it with a for loop like this pseudo code:



temp = [None , None, None, None]
i = 0
for id in idList:
temp[i] = table.filter(table['ID'] == id)
i += 1


but it took a long time to do so.
is there any filter or library which do this fast? what should I insert in my code? I need something in pyspark










share|improve this question
























  • Do you want 4 different tables for 1, 47, 54 and 89 respectively? Secondly, you use id in the for loop and then use temp[i]? i is undefined. You mention that it took you a lot of time, so did you try it in PySpark?

    – cph_sto
    2 days ago












  • i is iteration counter and that's pseudo code. yes, I need exactly that for tables and in pyspark it took a long time to be done.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago












  • i is not a problem, the problem is to select that 4 tables.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago











  • Your pseudo-code looks fine though.

    – cph_sto
    2 days ago











  • Check this - may be this solves your problem, though the logic used is quite similar, but with dictionary instead. stackoverflow.com/questions/54743574/…

    – cph_sto
    2 days ago















0















I have a table in spark, which has ID and numOfReq attributes.
in ID, it is between 1 to 100 and it's not in order, and each ID can be repeated many times in the table. I want to extract rows with 1, 47, 54 and 89 IDs. I can do it with a for loop like this pseudo code:



temp = [None , None, None, None]
i = 0
for id in idList:
temp[i] = table.filter(table['ID'] == id)
i += 1


but it took a long time to do so.
is there any filter or library which do this fast? what should I insert in my code? I need something in pyspark










share|improve this question
























  • Do you want 4 different tables for 1, 47, 54 and 89 respectively? Secondly, you use id in the for loop and then use temp[i]? i is undefined. You mention that it took you a lot of time, so did you try it in PySpark?

    – cph_sto
    2 days ago












  • i is iteration counter and that's pseudo code. yes, I need exactly that for tables and in pyspark it took a long time to be done.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago












  • i is not a problem, the problem is to select that 4 tables.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago











  • Your pseudo-code looks fine though.

    – cph_sto
    2 days ago











  • Check this - may be this solves your problem, though the logic used is quite similar, but with dictionary instead. stackoverflow.com/questions/54743574/…

    – cph_sto
    2 days ago













0












0








0








I have a table in spark, which has ID and numOfReq attributes.
in ID, it is between 1 to 100 and it's not in order, and each ID can be repeated many times in the table. I want to extract rows with 1, 47, 54 and 89 IDs. I can do it with a for loop like this pseudo code:



temp = [None , None, None, None]
i = 0
for id in idList:
temp[i] = table.filter(table['ID'] == id)
i += 1


but it took a long time to do so.
is there any filter or library which do this fast? what should I insert in my code? I need something in pyspark










share|improve this question
















I have a table in spark, which has ID and numOfReq attributes.
in ID, it is between 1 to 100 and it's not in order, and each ID can be repeated many times in the table. I want to extract rows with 1, 47, 54 and 89 IDs. I can do it with a for loop like this pseudo code:



temp = [None , None, None, None]
i = 0
for id in idList:
temp[i] = table.filter(table['ID'] == id)
i += 1


but it took a long time to do so.
is there any filter or library which do this fast? what should I insert in my code? I need something in pyspark







python pyspark






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 2 days ago







Mohammad Hassan Bigdeli Shamlo

















asked 2 days ago









Mohammad Hassan Bigdeli ShamloMohammad Hassan Bigdeli Shamlo

175




175












  • Do you want 4 different tables for 1, 47, 54 and 89 respectively? Secondly, you use id in the for loop and then use temp[i]? i is undefined. You mention that it took you a lot of time, so did you try it in PySpark?

    – cph_sto
    2 days ago












  • i is iteration counter and that's pseudo code. yes, I need exactly that for tables and in pyspark it took a long time to be done.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago












  • i is not a problem, the problem is to select that 4 tables.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago











  • Your pseudo-code looks fine though.

    – cph_sto
    2 days ago











  • Check this - may be this solves your problem, though the logic used is quite similar, but with dictionary instead. stackoverflow.com/questions/54743574/…

    – cph_sto
    2 days ago

















  • Do you want 4 different tables for 1, 47, 54 and 89 respectively? Secondly, you use id in the for loop and then use temp[i]? i is undefined. You mention that it took you a lot of time, so did you try it in PySpark?

    – cph_sto
    2 days ago












  • i is iteration counter and that's pseudo code. yes, I need exactly that for tables and in pyspark it took a long time to be done.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago












  • i is not a problem, the problem is to select that 4 tables.

    – Mohammad Hassan Bigdeli Shamlo
    2 days ago











  • Your pseudo-code looks fine though.

    – cph_sto
    2 days ago











  • Check this - may be this solves your problem, though the logic used is quite similar, but with dictionary instead. stackoverflow.com/questions/54743574/…

    – cph_sto
    2 days ago
















Do you want 4 different tables for 1, 47, 54 and 89 respectively? Secondly, you use id in the for loop and then use temp[i]? i is undefined. You mention that it took you a lot of time, so did you try it in PySpark?

– cph_sto
2 days ago






Do you want 4 different tables for 1, 47, 54 and 89 respectively? Secondly, you use id in the for loop and then use temp[i]? i is undefined. You mention that it took you a lot of time, so did you try it in PySpark?

– cph_sto
2 days ago














i is iteration counter and that's pseudo code. yes, I need exactly that for tables and in pyspark it took a long time to be done.

– Mohammad Hassan Bigdeli Shamlo
2 days ago






i is iteration counter and that's pseudo code. yes, I need exactly that for tables and in pyspark it took a long time to be done.

– Mohammad Hassan Bigdeli Shamlo
2 days ago














i is not a problem, the problem is to select that 4 tables.

– Mohammad Hassan Bigdeli Shamlo
2 days ago





i is not a problem, the problem is to select that 4 tables.

– Mohammad Hassan Bigdeli Shamlo
2 days ago













Your pseudo-code looks fine though.

– cph_sto
2 days ago





Your pseudo-code looks fine though.

– cph_sto
2 days ago













Check this - may be this solves your problem, though the logic used is quite similar, but with dictionary instead. stackoverflow.com/questions/54743574/…

– cph_sto
2 days ago





Check this - may be this solves your problem, though the logic used is quite similar, but with dictionary instead. stackoverflow.com/questions/54743574/…

– cph_sto
2 days ago












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