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https://issues.apache.org/jira/browse/HIVE-10165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14485920#comment-14485920
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Alan Gates commented on HIVE-10165:
-----------------------------------
I've reviewed the general class structure. Everything looks reasonable. I'll
hold off on reviewing the implementing code until there are tests and at least
one implementation of RecordMutator, as I assume those will force some changes.
bq. 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.
Why is this leading to inconsistent data? I can't see why it should.
[~roshan_naik], [~owen.omalley], you might be interested to review this as
well.
> 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
> Fix For: 1.2.0
>
> Attachments: HIVE-10165.0.patch, ReflectiveOperationWriter.java
>
>
> 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}}.
> * 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].
> h3. Example
> I've attached simple typical usage of the API. This is not a patch and is
> intended as an illustration only: [^ReflectiveOperationWriter.java]
> h3. Known issues
> I have not yet provided any unit tests for the extended functionality. I
> fully expect that tests are required and will work on these if my patches
> have merit.
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