Optimization of PostgreSQL ETL Processing Pipeline Unicorn Meta Zoo #1: Why another podcast? ...

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Optimization of PostgreSQL ETL Processing Pipeline



Unicorn Meta Zoo #1: Why another podcast?
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I’m looking for suggestions to create several different postgresql.conf versions: one optimized for Writing, the second optimized for Reading.



Context



I ETL dozens of very large (multi-GB) text files into PostgreSQL 11. The process is repeated twice a month for some datasets, and monthly for other datasets. Then I replicate the local database tables to a cloud-based server for subscribers to access.



Step 01: Local Processing Server



This is an iMac 27 with 64GB in RAM and a 01 TB SSD disk.
I have an instance of PostgreSQL 11 with the data directory stored in the SSD. This is the "Local SSD Instance".



At this stage I take raw text files and insert the records into PostgreSQL (using either the fantastic pgLoader or my own custom Python code). Then there’s significant post-processing: indexing of fields; many UPDATES; cross-referencing data; and geocoding records.



This process is totally hardware-bound. And I wrote (what I think is) a writing-optimized postgresql.conf file, below. My goal is to optimize PostgreSQL for fast writing (no WAL, huge checkpoint intervals, etc). At this stage I don’t care about crash protection.



In addition, during the ETL process, I use SQL table-creation commands like:




  • low FILLFACTOR (“in heavily updated tables smaller fillfactors are appropriate.”)

  • CREATE UNLOGGED TABLE


Is there a way to load the entire PostgreSQL application into RAM and perform all operations (raw data loading, indexing, field enrichment) in RAM? Once finished, save data files back to SSD.



Step 02: Transfer to Local Repository



Once a large table is loaded, indexed, and post-processed in Step 01 above I replicate the table to a second local instance of PostgreSQL 11 where the data directory is stored in an external 16 TB Thunderbolt 3 disk, the "Local Thunderbolt 3 Instance". My iMac does not have enough SSD storage to hold all the tables in the SSD.



This is the command I use to transfer a table from "Local SSD Instance" to "Local Thunderbolt 3 Instance":



pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


One problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. Is there another way to transfer the tables from "Local SSD Instance" to "Local Thunderbolt 3 Instance" without re-indexing every table?



No, I don’t want to transfer tables directly from "Local SSD Instance" to the remote server. I need to have a local repository of all tables as there will be multiple cloud-based instances with different variations of the individual loaded tables.



I read somewhere that transfering a table to a different server somehow "compacts" the data so that I don’t need to run VACUUM on the target table. Is this correct? Or do I still need to run VACUUM after re-indexing the table?



Step 03: Replicate data to cloud-based server



I have set up a "Droplet" in Digital Ocean with 48 GB Memory, 960 GB Disk + 1.66 TB attached storage, running Ubuntu 18.04.2 x64. Here I’m running PostgreSQL 11 as well.



The postgresql.conf file needs to be optimized for writing as I need to transfer over 100 tables with over 1.5 TB of data as quickly as possible. In this step I take individual tables from the "Local Thunderbolt 3 Instance" and transfer the tables to Digital Ocean’s droplet.



The table transfer command I use is:



pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


But a problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. How can I accelerate the process of transferring tables to the remote server?



Step 04: Optimize cloud-based server for Reading.



Once all the tables have been transferred, I need to change the postgresql.conf file and use a read-optimized configuration.



The read-optimized configuration needs to provide the fastest possible response rates to PostgreSQL queries. Any suggestions?



My Questions:




  • How to create a write-optimized postgresql.conf file?

  • How to create a read-optimized postgresql.conf file?

  • How to transfer tables to different server without re-indexing at the target server?


Thanks.



# Writing-optimized postgresql.conf file:
#
# WAL:
wal_level = minimal
max_wal_size = 10GB
wal_buffers = 16MB
archive_mode = off
max_wal_senders = 0
#
# Memory:
shared_buffers = 1280MB
temp_buffers = 800MB
work_mem = 400MB
maintenance_work_mem = 640MB
dynamic_shared_memory_type = posix
#
autovacuum = off
bonjour = off
checkpoint_completion_target = 0.9
default_statistics_target = 1000
effective_cache_size = 4GB
#
synchronous_commit = off
#
random_page_cost = 1
seq_page_cost = 1









share|improve this question







New contributor




Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.



























    0















    I’m looking for suggestions to create several different postgresql.conf versions: one optimized for Writing, the second optimized for Reading.



    Context



    I ETL dozens of very large (multi-GB) text files into PostgreSQL 11. The process is repeated twice a month for some datasets, and monthly for other datasets. Then I replicate the local database tables to a cloud-based server for subscribers to access.



    Step 01: Local Processing Server



    This is an iMac 27 with 64GB in RAM and a 01 TB SSD disk.
    I have an instance of PostgreSQL 11 with the data directory stored in the SSD. This is the "Local SSD Instance".



    At this stage I take raw text files and insert the records into PostgreSQL (using either the fantastic pgLoader or my own custom Python code). Then there’s significant post-processing: indexing of fields; many UPDATES; cross-referencing data; and geocoding records.



    This process is totally hardware-bound. And I wrote (what I think is) a writing-optimized postgresql.conf file, below. My goal is to optimize PostgreSQL for fast writing (no WAL, huge checkpoint intervals, etc). At this stage I don’t care about crash protection.



    In addition, during the ETL process, I use SQL table-creation commands like:




    • low FILLFACTOR (“in heavily updated tables smaller fillfactors are appropriate.”)

    • CREATE UNLOGGED TABLE


    Is there a way to load the entire PostgreSQL application into RAM and perform all operations (raw data loading, indexing, field enrichment) in RAM? Once finished, save data files back to SSD.



    Step 02: Transfer to Local Repository



    Once a large table is loaded, indexed, and post-processed in Step 01 above I replicate the table to a second local instance of PostgreSQL 11 where the data directory is stored in an external 16 TB Thunderbolt 3 disk, the "Local Thunderbolt 3 Instance". My iMac does not have enough SSD storage to hold all the tables in the SSD.



    This is the command I use to transfer a table from "Local SSD Instance" to "Local Thunderbolt 3 Instance":



    pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


    One problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. Is there another way to transfer the tables from "Local SSD Instance" to "Local Thunderbolt 3 Instance" without re-indexing every table?



    No, I don’t want to transfer tables directly from "Local SSD Instance" to the remote server. I need to have a local repository of all tables as there will be multiple cloud-based instances with different variations of the individual loaded tables.



    I read somewhere that transfering a table to a different server somehow "compacts" the data so that I don’t need to run VACUUM on the target table. Is this correct? Or do I still need to run VACUUM after re-indexing the table?



    Step 03: Replicate data to cloud-based server



    I have set up a "Droplet" in Digital Ocean with 48 GB Memory, 960 GB Disk + 1.66 TB attached storage, running Ubuntu 18.04.2 x64. Here I’m running PostgreSQL 11 as well.



    The postgresql.conf file needs to be optimized for writing as I need to transfer over 100 tables with over 1.5 TB of data as quickly as possible. In this step I take individual tables from the "Local Thunderbolt 3 Instance" and transfer the tables to Digital Ocean’s droplet.



    The table transfer command I use is:



    pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


    But a problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. How can I accelerate the process of transferring tables to the remote server?



    Step 04: Optimize cloud-based server for Reading.



    Once all the tables have been transferred, I need to change the postgresql.conf file and use a read-optimized configuration.



    The read-optimized configuration needs to provide the fastest possible response rates to PostgreSQL queries. Any suggestions?



    My Questions:




    • How to create a write-optimized postgresql.conf file?

    • How to create a read-optimized postgresql.conf file?

    • How to transfer tables to different server without re-indexing at the target server?


    Thanks.



    # Writing-optimized postgresql.conf file:
    #
    # WAL:
    wal_level = minimal
    max_wal_size = 10GB
    wal_buffers = 16MB
    archive_mode = off
    max_wal_senders = 0
    #
    # Memory:
    shared_buffers = 1280MB
    temp_buffers = 800MB
    work_mem = 400MB
    maintenance_work_mem = 640MB
    dynamic_shared_memory_type = posix
    #
    autovacuum = off
    bonjour = off
    checkpoint_completion_target = 0.9
    default_statistics_target = 1000
    effective_cache_size = 4GB
    #
    synchronous_commit = off
    #
    random_page_cost = 1
    seq_page_cost = 1









    share|improve this question







    New contributor




    Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.























      0












      0








      0








      I’m looking for suggestions to create several different postgresql.conf versions: one optimized for Writing, the second optimized for Reading.



      Context



      I ETL dozens of very large (multi-GB) text files into PostgreSQL 11. The process is repeated twice a month for some datasets, and monthly for other datasets. Then I replicate the local database tables to a cloud-based server for subscribers to access.



      Step 01: Local Processing Server



      This is an iMac 27 with 64GB in RAM and a 01 TB SSD disk.
      I have an instance of PostgreSQL 11 with the data directory stored in the SSD. This is the "Local SSD Instance".



      At this stage I take raw text files and insert the records into PostgreSQL (using either the fantastic pgLoader or my own custom Python code). Then there’s significant post-processing: indexing of fields; many UPDATES; cross-referencing data; and geocoding records.



      This process is totally hardware-bound. And I wrote (what I think is) a writing-optimized postgresql.conf file, below. My goal is to optimize PostgreSQL for fast writing (no WAL, huge checkpoint intervals, etc). At this stage I don’t care about crash protection.



      In addition, during the ETL process, I use SQL table-creation commands like:




      • low FILLFACTOR (“in heavily updated tables smaller fillfactors are appropriate.”)

      • CREATE UNLOGGED TABLE


      Is there a way to load the entire PostgreSQL application into RAM and perform all operations (raw data loading, indexing, field enrichment) in RAM? Once finished, save data files back to SSD.



      Step 02: Transfer to Local Repository



      Once a large table is loaded, indexed, and post-processed in Step 01 above I replicate the table to a second local instance of PostgreSQL 11 where the data directory is stored in an external 16 TB Thunderbolt 3 disk, the "Local Thunderbolt 3 Instance". My iMac does not have enough SSD storage to hold all the tables in the SSD.



      This is the command I use to transfer a table from "Local SSD Instance" to "Local Thunderbolt 3 Instance":



      pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


      One problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. Is there another way to transfer the tables from "Local SSD Instance" to "Local Thunderbolt 3 Instance" without re-indexing every table?



      No, I don’t want to transfer tables directly from "Local SSD Instance" to the remote server. I need to have a local repository of all tables as there will be multiple cloud-based instances with different variations of the individual loaded tables.



      I read somewhere that transfering a table to a different server somehow "compacts" the data so that I don’t need to run VACUUM on the target table. Is this correct? Or do I still need to run VACUUM after re-indexing the table?



      Step 03: Replicate data to cloud-based server



      I have set up a "Droplet" in Digital Ocean with 48 GB Memory, 960 GB Disk + 1.66 TB attached storage, running Ubuntu 18.04.2 x64. Here I’m running PostgreSQL 11 as well.



      The postgresql.conf file needs to be optimized for writing as I need to transfer over 100 tables with over 1.5 TB of data as quickly as possible. In this step I take individual tables from the "Local Thunderbolt 3 Instance" and transfer the tables to Digital Ocean’s droplet.



      The table transfer command I use is:



      pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


      But a problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. How can I accelerate the process of transferring tables to the remote server?



      Step 04: Optimize cloud-based server for Reading.



      Once all the tables have been transferred, I need to change the postgresql.conf file and use a read-optimized configuration.



      The read-optimized configuration needs to provide the fastest possible response rates to PostgreSQL queries. Any suggestions?



      My Questions:




      • How to create a write-optimized postgresql.conf file?

      • How to create a read-optimized postgresql.conf file?

      • How to transfer tables to different server without re-indexing at the target server?


      Thanks.



      # Writing-optimized postgresql.conf file:
      #
      # WAL:
      wal_level = minimal
      max_wal_size = 10GB
      wal_buffers = 16MB
      archive_mode = off
      max_wal_senders = 0
      #
      # Memory:
      shared_buffers = 1280MB
      temp_buffers = 800MB
      work_mem = 400MB
      maintenance_work_mem = 640MB
      dynamic_shared_memory_type = posix
      #
      autovacuum = off
      bonjour = off
      checkpoint_completion_target = 0.9
      default_statistics_target = 1000
      effective_cache_size = 4GB
      #
      synchronous_commit = off
      #
      random_page_cost = 1
      seq_page_cost = 1









      share|improve this question







      New contributor




      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.












      I’m looking for suggestions to create several different postgresql.conf versions: one optimized for Writing, the second optimized for Reading.



      Context



      I ETL dozens of very large (multi-GB) text files into PostgreSQL 11. The process is repeated twice a month for some datasets, and monthly for other datasets. Then I replicate the local database tables to a cloud-based server for subscribers to access.



      Step 01: Local Processing Server



      This is an iMac 27 with 64GB in RAM and a 01 TB SSD disk.
      I have an instance of PostgreSQL 11 with the data directory stored in the SSD. This is the "Local SSD Instance".



      At this stage I take raw text files and insert the records into PostgreSQL (using either the fantastic pgLoader or my own custom Python code). Then there’s significant post-processing: indexing of fields; many UPDATES; cross-referencing data; and geocoding records.



      This process is totally hardware-bound. And I wrote (what I think is) a writing-optimized postgresql.conf file, below. My goal is to optimize PostgreSQL for fast writing (no WAL, huge checkpoint intervals, etc). At this stage I don’t care about crash protection.



      In addition, during the ETL process, I use SQL table-creation commands like:




      • low FILLFACTOR (“in heavily updated tables smaller fillfactors are appropriate.”)

      • CREATE UNLOGGED TABLE


      Is there a way to load the entire PostgreSQL application into RAM and perform all operations (raw data loading, indexing, field enrichment) in RAM? Once finished, save data files back to SSD.



      Step 02: Transfer to Local Repository



      Once a large table is loaded, indexed, and post-processed in Step 01 above I replicate the table to a second local instance of PostgreSQL 11 where the data directory is stored in an external 16 TB Thunderbolt 3 disk, the "Local Thunderbolt 3 Instance". My iMac does not have enough SSD storage to hold all the tables in the SSD.



      This is the command I use to transfer a table from "Local SSD Instance" to "Local Thunderbolt 3 Instance":



      pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


      One problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. Is there another way to transfer the tables from "Local SSD Instance" to "Local Thunderbolt 3 Instance" without re-indexing every table?



      No, I don’t want to transfer tables directly from "Local SSD Instance" to the remote server. I need to have a local repository of all tables as there will be multiple cloud-based instances with different variations of the individual loaded tables.



      I read somewhere that transfering a table to a different server somehow "compacts" the data so that I don’t need to run VACUUM on the target table. Is this correct? Or do I still need to run VACUUM after re-indexing the table?



      Step 03: Replicate data to cloud-based server



      I have set up a "Droplet" in Digital Ocean with 48 GB Memory, 960 GB Disk + 1.66 TB attached storage, running Ubuntu 18.04.2 x64. Here I’m running PostgreSQL 11 as well.



      The postgresql.conf file needs to be optimized for writing as I need to transfer over 100 tables with over 1.5 TB of data as quickly as possible. In this step I take individual tables from the "Local Thunderbolt 3 Instance" and transfer the tables to Digital Ocean’s droplet.



      The table transfer command I use is:



      pg_dump postgresql://<Username>:<Password>@<Source_IP>:<Source_Port>/<Source_Database> -t '<Table_Name>_*' | psql postgresql://<Username>:<Password>@<Target_IP>:<Target_Port>/<Target_Database>


      But a problem here is that each index is recreated after the actual records are transferred. The re-indexing takes a lot of time. How can I accelerate the process of transferring tables to the remote server?



      Step 04: Optimize cloud-based server for Reading.



      Once all the tables have been transferred, I need to change the postgresql.conf file and use a read-optimized configuration.



      The read-optimized configuration needs to provide the fastest possible response rates to PostgreSQL queries. Any suggestions?



      My Questions:




      • How to create a write-optimized postgresql.conf file?

      • How to create a read-optimized postgresql.conf file?

      • How to transfer tables to different server without re-indexing at the target server?


      Thanks.



      # Writing-optimized postgresql.conf file:
      #
      # WAL:
      wal_level = minimal
      max_wal_size = 10GB
      wal_buffers = 16MB
      archive_mode = off
      max_wal_senders = 0
      #
      # Memory:
      shared_buffers = 1280MB
      temp_buffers = 800MB
      work_mem = 400MB
      maintenance_work_mem = 640MB
      dynamic_shared_memory_type = posix
      #
      autovacuum = off
      bonjour = off
      checkpoint_completion_target = 0.9
      default_statistics_target = 1000
      effective_cache_size = 4GB
      #
      synchronous_commit = off
      #
      random_page_cost = 1
      seq_page_cost = 1






      ssd performance database postgresql replication






      share|improve this question







      New contributor




      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question







      New contributor




      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      share|improve this question




      share|improve this question






      New contributor




      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      asked 11 hours ago









      Jose CLlJose CLl

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      New contributor




      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.





      New contributor





      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      Jose CLl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






















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