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https://issues.apache.org/jira/browse/GOBBLIN-865?focusedWorklogId=316381&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-316381
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ASF GitHub Bot logged work on GOBBLIN-865:
------------------------------------------
Author: ASF GitHub Bot
Created on: 23/Sep/19 02:32
Start Date: 23/Sep/19 02:32
Worklog Time Spent: 10m
Work Description: htran1 commented on pull request #2722: GOBBLIN-865:
Add feature that enables PK-chunking in partition
URL: https://github.com/apache/incubator-gobblin/pull/2722#discussion_r326307389
##########
File path:
gobblin-salesforce/src/main/java/org/apache/gobblin/salesforce/SalesforceExtractor.java
##########
@@ -869,7 +862,7 @@ public SalesforceBulkJobId
getQueryResultIdsPkChunking(String entity, List<Predi
// wait for completion, failure, or formation of PK chunking batches
while ((bulkBatchInfo.getState() != BatchStateEnum.Completed)
&& (bulkBatchInfo.getState() != BatchStateEnum.Failed)
- && (!usingPkChunking || bulkBatchInfo.getState() !=
BatchStateEnum.NotProcessed)) {
+ && (bulkBatchInfo.getState() != BatchStateEnum.NotProcessed)) {
Review comment:
Is skipping over this state safe for the non-pk chunking case? Could it be a
valid waiting
or error state for non-pk chunking queries?
I think we should raise an error if there are any NotProcessed batches and
if there are more than one NotProcessed batches for PK chunking mode since that
indicates some expected work was not performed and there may be data loss if we
move the checkpoint forward.
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Issue Time Tracking
-------------------
Worklog Id: (was: 316381)
Time Spent: 7.5h (was: 7h 20m)
> Add feature that enables PK-chunking in partition
> --------------------------------------------------
>
> Key: GOBBLIN-865
> URL: https://issues.apache.org/jira/browse/GOBBLIN-865
> Project: Apache Gobblin
> Issue Type: Task
> Reporter: Alex Li
> Priority: Major
> Labels: salesforce
> Time Spent: 7.5h
> Remaining Estimate: 0h
>
> In SFDC(salesforce) connector, we have partitioning mechanisms to split a
> giant query to multiple sub queries. There are 3 mechanisms:
> * simple partition (equally split by time)
> * dynamic pre-partition (generate histogram and split by row numbers)
> * user specified partition (set up time range in job file)
> However there are tables like Task and Contract are failing time to time to
> fetch full data.
> We may want to utilize PK-chunking to partition the query.
>
> The pk-chunking doc from SFDC -
> [https://developer.salesforce.com/docs/atlas.en-us.api_asynch.meta/api_asynch/async_api_headers_enable_pk_chunking.htm]
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