Yes, updates and deletes is trouble. At the moment for updates collection we refresh result data by query to C* (java driver) before reporting to user. For deletes we can skip it during scanning by TTL for example (not tested yet).

On 09/16/2014 04:53 PM, moshe.kr...@barclays.com wrote:

You will also have to read/resolve multiple row instances (if you update records) and tombstones (if you delete records) yourself.

*From:*platon.tema [mailto:platon.t...@yandex.ru]
*Sent:* Tuesday, September 16, 2014 1:51 PM
*To:* user@cassandra.apache.org
*Subject:* Re: Direct IO with Spark and Hadoop over Cassandra

Thanks.

But 1) overcomes with C* API for commitlog and memtables or with mixed access (direct IO + traditional connectors or pure CQL if data model allows, we experimented with it).

2) is more complex for universal solution. In our case C* uses without replication (RF=1) because of huge data size (replication too expensive).

On 09/16/2014 03:40 PM, DuyHai Doan wrote:

    If you access directly the C* sstables from those frameworks, you
    will:

    1) miss live data which are in memory and not dumped yet to disk

    2) skip the Dynamo layer of C* responsible for data consistency

    Le 16 sept. 2014 10:58, "platon.tema" <platon.t...@yandex.ru
    <mailto:platon.t...@yandex.ru>> a écrit :

    Hi.

    As I see massive data processing tools (map\reduce) with C* data
    include

    connectors
    - Calliope http://tuplejump.github.io/calliope/
    - Datastax spark cassandra connector
    https://github.com/datastax/spark-cassandra-connector
    - Startio Deep https://github.com/Stratio/stratio-deep
    - other free\commercial

    runtime (job management and infrastructure)
    - Spark
    - Hadoop

    But if I'm not mistaken all these solutions use network for data
    loading. In best case logic instance (some "job") run on the same
    node (wherethe corresponding range was found).

    Why this logic can`t use direct C* IO (sstable reading from disk)?
    Any cons ?

    Some time ago i read article (still can't find it) about
    academical research within Hadoop was modified to support this
    direct IO mode. According to that benchmarks direct IOgave a
    significant performance increase.

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