Hi,

Can someone in a nutshell explain *the *Hbase use of log-structured
merge-tree (LSM-tree) as data storage architecture

The idea of merging smaller files to larger files periodically to reduce
disk seeks,  is this similar concept to compaction in HDFS or Hive?

Thanks


Dr Mich Talebzadeh



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On 21 October 2016 at 15:27, Mich Talebzadeh <mich.talebza...@gmail.com>
wrote:

> Sorry that should read Hive not Spark here
>
> Say compared to Spark that is basically a SQL layer relying on different
> engines (mr, Tez, Spark) to execute the code
>
> Dr Mich Talebzadeh
>
>
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> On 21 October 2016 at 13:17, Ted Yu <yuzhih...@gmail.com> wrote:
>
>> Mich:
>> Here is brief description of hbase architecture:
>> https://hbase.apache.org/book.html#arch.overview
>>
>> You can also get more details from Lars George's or Nick Dimiduk's books.
>>
>> HBase doesn't support SQL directly. There is no cost based optimization.
>>
>> Cheers
>>
>> > On Oct 21, 2016, at 1:43 AM, Mich Talebzadeh <mich.talebza...@gmail.com>
>> wrote:
>> >
>> > Hi,
>> >
>> > This is a general question.
>> >
>> > Is Hbase fast because Hbase uses Hash tables and provides random access,
>> > and it stores the data in indexed HDFS files for faster lookups.
>> >
>> > Say compared to Spark that is basically a SQL layer relying on different
>> > engines (mr, Tez, Spark) to execute the code (although it has Cost Base
>> > Optimizer), how Hbase fares, beyond relying on these engines
>> >
>> > Thanks
>> >
>> >
>> > Dr Mich Talebzadeh
>> >
>> >
>> >
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