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HBase, mail # user - [ANNOUNCE] Phoenix v 2.1 released


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Re: [ANNOUNCE] Phoenix v 2.1 released
Asaf Mesika 2013-10-28, 18:14
I couldn't get the Row Value Constructor feature.
Do you perhaps have a real world use case to demonstrate this?

On Friday, October 25, 2013, James Taylor wrote:

> The Phoenix team is pleased to announce the immediate availability of
> Phoenix 2.1 [1].
> More than 20 individuals contributed to the release. Here are some of the
> new features
> now available:
> * Secondary Indexing [2] to create and automatically maintain global
> indexes over your
>    primary table.
>    - Queries automatically use an index when more efficient, turning your
> full table scans
>      into point and range scans.
>    - Multiple columns may be indexed in ascending or descending sort order.
>    - Additional primary table columns may be included in the index to form
> a covered
>      index.
>    - Available in two flavors:
>         o Server-side index maintenance for mutable data.
>         o Client-side index maintenance optimized for write-once,
> append-only use cases.
> * Row Value Constructors [3], a standard SQL construct to efficiently
> locate the row at
>   or after a composite key value.
>    - Enables a query-more capability to efficiently step through your data.
>    - Optimizes IN list of composite key values to be point gets.
> * Map-reduce based CSV Bulk Loader [4] to build Phoenix-compliant HFiles
> and load
>   them into HBase.
> * MD5 hash and INVERT built-in functions
>
> Phoenix 2.1 requires HBase 0.94.4 or above, with 0.94.10 or above required
> for mutable secondary indexing. For the best performance, we recommend
> HBase 0.94.12 or above.
>
> Regards,
>
> James
> @JamesPlusPlus
> http://phoenix-hbase.blogspot.com/
>
> [1] https://github.com/forcedotcom/phoenix/wiki/Download
> [2] https://github.com/forcedotcom/phoenix/wiki/Secondary-Indexing
> [3] https://github.com/forcedotcom/phoenix/wiki/Row-Value-Constructors
> [4]
>
> https://github.com/forcedotcom/phoenix/wiki/Bulk-CSV-loading-through-map-reduce
>