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From "Jeffrey Zhong (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-10999) Cross-row Transaction : Implement Percolator Algorithm on HBase
Date Wed, 28 May 2014 02:04:04 GMT

    [ https://issues.apache.org/jira/browse/HBASE-10999?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14010663#comment-14010663

Jeffrey Zhong commented on HBASE-10999:

[~cuijianwei] It seems the WorkerRegister hasn't fully been implemented. The current code
is based on 0.94 while Hbase CP has incompatible changes since then. 
What's your plan to incorporate Themis into HBase: move the code into HBase code base or still
put Themis as a third party library outside of HBase. If leaving Themis outside, I can image
transaction will become one of core functionalities and will be hard to fix when there is
any issue and also hard to correlate release cycles.  [~saint.ack@gmail.com] What's your thoughts
on this? Thanks.

> Cross-row Transaction : Implement Percolator Algorithm on HBase
> ---------------------------------------------------------------
>                 Key: HBASE-10999
>                 URL: https://issues.apache.org/jira/browse/HBASE-10999
>             Project: HBase
>          Issue Type: New Feature
>          Components: Transactions/MVCC
>    Affects Versions: 0.99.0
>            Reporter: cuijianwei
>            Assignee: cuijianwei
> Cross-row transaction is a desired function for database. It is not easy to keep ACID
characteristics of cross-row transactions in distribute databases such as HBase, because data
of cross-transaction might locate in different machines. In the paper http://research.google.com/pubs/pub36726.html,
google presents an algorithm(named percolator) to implement cross-row transactions on BigTable.
After analyzing the algorithm, we found percolator might also be a choice to provide cross-row
transaction on HBase. The reasons includes:
> 1. Percolator could keep the ACID of cross-row transaction as described in google's paper.
Percolator depends on a Global Incremental Timestamp Service to define the order of transactions,
this is important to keep ACID of transaction.
> 2. Percolator algorithm could be totally implemented in client-side. This means we do
not need to change the logic of server side. Users could easily include percolator in their
client and adopt percolator APIs only when they want cross-row transaction.
> 3. Percolator is a general algorithm which could be implemented based on databases providing
single-row transaction. Therefore, it is feasible to implement percolator on HBase.
> In last few months, we have implemented percolator on HBase, did correctness validation,
performance test and finally successfully applied this algorithm in our production environment.
Our works include:
> 1. percolator algorithm implementation on HBase. The current implementations includes:
>     a). a Transaction module to provides put/delete/get/scan interfaces to do cross-row/cross-table
>     b). a Global Incremental Timestamp Server to provide globally monotonically increasing
timestamp for transaction.
>     c). a LockCleaner module to resolve conflict when concurrent transactions mutate
the same column.
>     d). an internal module to implement prewrite/commit/get/scan logic of percolator.
>    Although percolator logic could be totally implemented in client-side, we use coprocessor
framework of HBase in our implementation. This is because coprocessor could provide percolator-specific
Rpc interfaces such as prewrite/commit to reduce Rpc rounds and improve efficiency. Another
reason to use coprocessor is that we want to decouple percolator's code from HBase so that
users will get clean HBase code if they don't need cross-row transactions. In future, we will
also explore the concurrent running characteristic of coprocessor to do cross-row mutations
more efficiently.
> 2. an AccountTransfer simulation program to validate the correctness of implementation.
This program will distribute initial values in different tables, rows and columns in HBase.
Each column represents an account. Then, configured client threads will be concurrently started
to read out a number of account values from different tables and rows by percolator's get;
after this, clients will randomly transfer values among these accounts while keeping the sum
unchanged, which simulates concurrent cross-table/cross-row transactions. To check the correctness
of transactions, a checker thread will periodically scan account values from all columns,
make sure the current total value is the same as the initial total value. We run this validation
program while developing, this help us correct errors of implementation.
> 3. performance evaluation under various test situations. We compared percolator's APIs
with HBase's with different data size and client thread count for single-column transaction
which represents the worst performance case for percolator. We get the performance comparison
result as (below):
>     a) For read, the performance of percolator is 90% of HBase;
>     b) For write, the performance of percolator is 23%  of HBase.
> The drop derives from the overhead of percolator logic, the performance test result is
similar as the result reported by google's paper.
> 4. Performance improvement. The write performance of percolator decreases more compared
with HBase. This is because percolator's write needs to read data out to check write conflict
and needs two Rpcs which do prewriting and commiting respectively. We are investigating ways
to improve the write performance.
> We are glad to share current percolator implementation and hope this could provide a
choice for users who want cross-row transactions because it does not need to change the code
and logic of origin HBase. Comments and discussions are welcomed.

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