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https://issues.apache.org/jira/browse/HIVE-10165?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Elliot West updated HIVE-10165:
-------------------------------
Attachment: HIVE-10165.0.patch
I've attached (yet another) updated patch [^HIVE-10165.0.patch]. I do not
anticipate any further significant changes from my side at this time so I'd
appreciate a review when it's convenient. I've spent some time working on
Javadoc and tests. I'm fairly happy with the API currently and believe it is
fit for the ETL merge use-case.
I've reworked the larger scale tests (originally based on {{TestStreaming}}) so
that they are easier to read and construct. I also think that I now have a good
grasp on what is needed to factor out the commonalities between the Streaming
and Mutate implementations and improving upon the existing streaming tests and
coverage. That will be my next step assuming that the Mutate API is considered
to be 'on-track'.
> Improve hive-hcatalog-streaming extensibility and support updates and deletes.
> ------------------------------------------------------------------------------
>
> Key: HIVE-10165
> URL: https://issues.apache.org/jira/browse/HIVE-10165
> Project: Hive
> Issue Type: Improvement
> Components: HCatalog
> Reporter: Elliot West
> Assignee: Elliot West
> Labels: streaming_api
> Attachments: HIVE-10165.0.patch
>
>
> h3. Overview
> I'd like to extend the
> [hive-hcatalog-streaming|https://cwiki.apache.org/confluence/display/Hive/Streaming+Data+Ingest]
> API so that it also supports the writing of record updates and deletes in
> addition to the already supported inserts.
> h3. Motivation
> We have many Hadoop processes outside of Hive that merge changed facts into
> existing datasets. Traditionally we achieve this by: reading in a
> ground-truth dataset and a modified dataset, grouping by a key, sorting by a
> sequence and then applying a function to determine inserted, updated, and
> deleted rows. However, in our current scheme we must rewrite all partitions
> that may potentially contain changes. In practice the number of mutated
> records is very small when compared with the records contained in a
> partition. This approach results in a number of operational issues:
> * Excessive amount of write activity required for small data changes.
> * Downstream applications cannot robustly read these datasets while they are
> being updated.
> * Due to scale of the updates (hundreds or partitions) the scope for
> contention is high.
> I believe we can address this problem by instead writing only the changed
> records to a Hive transactional table. This should drastically reduce the
> amount of data that we need to write and also provide a means for managing
> concurrent access to the data. Our existing merge processes can read and
> retain each record's {{ROW_ID}}/{{RecordIdentifier}} and pass this through to
> an updated form of the hive-hcatalog-streaming API which will then have the
> required data to perform an update or insert in a transactional manner.
> h3. Benefits
> * Enables the creation of large-scale dataset merge processes
> * Opens up Hive transactional functionality in an accessible manner to
> processes that operate outside of Hive.
> h3. Implementation
> Our changes do not break the existing API contracts. Instead our approach has
> been to consider the functionality offered by the existing API and our
> proposed API as fulfilling separate and distinct use-cases. The existing API
> is primarily focused on the task of continuously writing large volumes of new
> data into a Hive table for near-immediate analysis. Our use-case however, is
> concerned more with the frequent but not continuous ingestion of mutations to
> a Hive table from some ETL merge process. Consequently we feel it is
> justifiable to add our new functionality via an alternative set of public
> interfaces and leave the existing API as is. This keeps both APIs clean and
> focused at the expense of presenting additional options to potential users.
> Wherever possible, shared implementation concerns have been factored out into
> abstract base classes that are open to third-party extension. A detailed
> breakdown of the changes is as follows:
> * We've introduced a public {{RecordMutator}} interface whose purpose is to
> expose insert/update/delete operations to the user. This is a counterpart to
> the write-only {{RecordWriter}}. We've also factored out life-cycle methods
> common to these two interfaces into a super {{RecordOperationWriter}}
> interface. Note that the row representation has be changed from {{byte[]}}
> to {{Object}}. Within our data processing jobs our records are often
> available in a strongly typed and decoded form such as a POJO or a Tuple
> object. Therefore is seems to make sense that we are able to pass this
> through to the {{OrcRecordUpdater}} without having to go through a {{byte[]}}
> encoding step. This of course still allows users to use {{byte[]}} if they
> wish.
> * The introduction of {{RecordMutator}} requires that insert/update/delete
> operations are then also exposed on a {{TransactionBatch}} type. We've done
> this with the introduction of a public {{MutatorTransactionBatch}} interface
> which is a counterpart to the write-only {{TransactionBatch}}. We've also
> factored out life-cycle methods common to these two interfaces into a super
> {{BaseTransactionBatch}} interface.
> * Functionality that would be shared by implementations of both
> {{RecordWriters}} and {{RecordMutators}} has been factored out of
> {{AbstractRecordWriter}} into a new abstract base class
> {{AbstractOperationRecordWriter}}. The visibility is such that it is open to
> extension by third parties. The {{AbstractOperationRecordWriter}} also
> permits the setting of the {{AcidOutputFormat.Options#recordIdColumn()}}
> (defaulted to {{-1}}) which is a requirement for enabling updates and
> deletes. Additionally, these options are now fed an {{ObjectInspector}} via
> an abstract method so that a {{SerDe}} is not mandated (it was not required
> for our use-case). The {{AbstractRecordWriter}} is now much leaner, handling
> only the extraction of the {{ObjectInspector}} from the {{SerDe}}.
> * A new abstract class, {{AbstractRecordMutator}} has been introduced to act
> as the base of concrete {{RecordMutator}} implementations. The key
> functionality added by this class is a validation step on {{update}} and
> {{delete}} to ensure that the record specified contains a
> {{RecordIdentifier}}. This was added as it is not explicitly checked for
> elsewhere and would otherwise generate an NPE deep down in
> {{OrcRecordUpdater}}.
> * There are now two private transaction batch implementations:
> {{HiveEndPoint.TransactionBatchImpl}} and its insert/update/delete
> counterpart: {{HiveEndPoint.MutationTransactionBatchImpl}}. As you might
> expect, {{TransactionBatchImpl}} must delegate to a {{RecordWriter}}
> implementation whereas {{MutationTransactionBatchImpl}} must delegates to a
> {{RecordMutator}} implementation. Shared transaction batch functionality has
> been factored out into an {{AbstractTransactionBatch}} class. In the case of
> {{MutationTransactionBatchImpl}} we've added a check to ensure that an error
> occurs should a user submit multiple types of operation to the same batch as
> we've found that this can lead to inconsistent data being returned from the
> underlying table when read from Hive.
> * To enable the usage of the different transaction batch variants we've added
> an additional transaction batch factory method to {{StreamingConnection}} and
> provided a suitable implementation in {{HiveEndPoint}}. It's worth noting
> that {{StreamingConnection}} is the only public facing component of the API
> contract that contains references to both the existing writer scheme and our
> mutator scheme.
> Please find this changes in the attached patch: [^HIVE-10165.0.patch].
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