[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17732943#comment-17732943 ] Enrico Minack commented on SPARK-19335: --- Created pull request for this: https://github.com/apache/spark/pull/41518 > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17605440#comment-17605440 ] Kboh commented on SPARK-19335: -- Also interested in this. ty > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.20.10#820010) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17520107#comment-17520107 ] Chandramouli Viswanathan commented on SPARK-19335: -- Hi Is the issue resolved? if yes, how can I get the sample implementation guide? to move forward. Thanks In Advance > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.20.1#820001) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17512998#comment-17512998 ] s4782 commented on SPARK-19335: --- Hi, is there any update on when this will be added? > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.20.1#820001) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17486391#comment-17486391 ] Charley Guillaume commented on SPARK-19335: --- This component would be of great value indeed! > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.20.1#820001) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17483162#comment-17483162 ] Hamza Khribi commented on SPARK-19335: -- Hello [~kevinyu98] , is there any news about this functionality? I believe its really essential for spark to support such functionality, i've been working with multiple clients where at some point they mix olap and oltp and its inevitable to do upserts on the business table giving the client's needs. Besides i think that deciding to resume working on this functionality based on this issue ticket( that is not easily identified by the community) is not enough. Thank you in advance, Best > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.20.1#820001) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17220856#comment-17220856 ] Denise Mauldin commented on SPARK-19335: [~kevinyu98] Using AWS Glue to copy/update data between two databases. We do not want to TRUNCATE the tables. We need to update every row in a table without modifying tables that have foreign keys to this table. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17220855#comment-17220855 ] Denise Mauldin commented on SPARK-19335: +1 This is a major deficiency for using Spark in ETL jobs. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17204565#comment-17204565 ] Simone commented on SPARK-19335: +1 it is really strange that Delta Lake offer this capability on parquet files and spark is not able to offer the same capability on an RDBMS. The success of delta lake clearly shows the need of UPSERT capabilities in spark. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17199617#comment-17199617 ] Aaron Lucas commented on SPARK-19335: - +1 this is a big feature that we are currently having to work around not having > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17199064#comment-17199064 ] Alex Hoffer commented on SPARK-19335: - +1, this would be really helpful. We have aggregates we'd like to upsert in a Postgres table. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17185643#comment-17185643 ] S commented on SPARK-19335: --- Efficient UPSERT using Spark DataFrame - is it available now? If yes, how can I get some samples and working direction? I am using later EMR > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17057469#comment-17057469 ] John Lonergan commented on SPARK-19335: --- Streaming continous data from a fire hose source into a JDBC store. Need batched commits for throughput, but also need batches size control to keep latency under control. ie Delayed commits but not too delayed. And I want to do this without risk of data loss in the event of losing the infra so the commits and checkpointing need to be aligned. Any examples of this in practice? Have this working in Flink with almost no effort, but would prefer Spark for consistency. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17001220#comment-17001220 ] Cory Lassila commented on SPARK-19335: -- +1 I believe this would be useful, my scenario is using a 5-min aggregate Spark Structured Streaming job which Reads from Kafka & uses forEachBatch to do multi-out to several different postgres tables. If we fail half-way thru multi-out writing to postgres, we get duplicate records in the postgres tables. Let me know if this makes sense or if I'm missing something. Thanks! > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16994166#comment-16994166 ] kevin yu commented on SPARK-19335: -- [~danny-seismic] [~Vdarshankb] [~nstudenski] [~mrayandutta] [~rinazbelhaj] [~drew222]: can you list the reasoning why your organization need this feature? We are assessing whether we should resume this work or not. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16993231#comment-16993231 ] Rinaz Belhaj commented on SPARK-19335: -- +1 This feature would be very useful. Any updates on this ? > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16904373#comment-16904373 ] Ayan Dutta commented on SPARK-19335: +1 This feature would be really useful > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian JIRA (v7.6.14#76016) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16834770#comment-16834770 ] Nicholas Studenski commented on SPARK-19335: +1 This feature would be very useful. > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16834024#comment-16834024 ] Darshan commented on SPARK-19335: - For some row level access related issue, our organisation allows to access kudu table via impala. We are connecting to kudu via impala jdbc. However, I am having constraint related to using dataframe to upsert data into kudu table. This feature will really help. Any updates on this? > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16826378#comment-16826378 ] Danny Guinther commented on SPARK-19335: Any update on this? Also, please forgive this dumb question, but I'm shocked that there's not more demand for this feature which makes me wonder if I have major misconceptions about Spark and its intended use. How do users survive without this functionality? I take it that the destination SQL database should have flexible up-time requirements allowing for drastic changes? The overwrite save mode is the only thing that offers anything like an UPDATE, but totally dropping/truncating the destination table seems inconceivable for many production environments. What am I missing? > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16592126#comment-16592126 ] kevin yu commented on SPARK-19335: -- [~drew222]: I am still working on it, right now, I am waiting for the data source v2 to be finished. Thanks. Kevin > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-19335) Spark should support doing an efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16592003#comment-16592003 ] drew zoellner commented on SPARK-19335: --- + 1 , is this still in progress? > Spark should support doing an efficient DataFrame Upsert via JDBC > - > > Key: SPARK-19335 > URL: https://issues.apache.org/jira/browse/SPARK-19335 > Project: Spark > Issue Type: Improvement >Reporter: Ilya Ganelin >Priority: Minor > > Doing a database update, as opposed to an insert is useful, particularly when > working with streaming applications which may require revisions to previously > stored data. > Spark DataFrames/DataSets do not currently support an Update feature via the > JDBC Writer allowing only Overwrite or Append. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
