Home | About | Sematext search-lucene.com search-hadoop.com
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB
 Search Hadoop and all its subprojects:

Switch to Threaded View
HBase >> mail # user >> schema help


Copy link to this message
-
Re: schema help
Thats very good to know.
I cant do the scan thru hbase shell?

On Thu, Aug 25, 2011 at 11:03 AM, Ian Varley <[EMAIL PROTECTED]> wrote:

> The rows don't need to be inserted in order; they're maintained in
> key-sorted order on the disk based on the architecture of HBase, which
> stores data sorted in memory and periodically flushes to immutable files in
> HDFS (which are later compacted to make read access more efficient). HBase
> keeps track of which physical files might contain a given key range, and
> only reads the ones it needs to.
>
> To do a query through the java API, you could create a scanner with a
> startrow that is the concatenation of your value for fieldA and the start
> time, and an endrow that has the current time.
>
> http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html
>
> Ian
>
> On Aug 25, 2011, at 9:53 AM, Rita wrote:
>
> Thanks for your reponse.
>
> 30 million rows is the best case :-)
>
> Couple of questions about doing, [fieldA][time] as my key:
>  Would I have to insert in order?
>  If no, how would hbase know to stop scanning the entire table?
>  How would a query actually look like, if my key was [fieldA time]?
>
> As a matter of fact, I can do 100% of my queries. I will leave the 5% out
> of my project/schema.
>
>
> On Thu, Aug 25, 2011 at 10:13 AM, Ian Varley <[EMAIL PROTECTED]
> <mailto:[EMAIL PROTECTED]>> wrote:
> Rita,
>
> There's no need to create separate tables here--the table is really just a
> "namespace" for keys. A better option would probably be having one table
> with "[fieldA][time]" (the two fields concatenated) as your row key. Then,
> you can seek directly to the start of your records in constant time, and
> then scan forward until you get to the end of the data (linear time in the
> size of data you expect to get back).
>
> The downside of this is that for the 5% of your queries that aren't in this
> form, you may have to do a full table scan. (Alternately, you could also
> maintain secondary indexes that help you get the data back with less than a
> full table scan; that would depend on the nature of the queries).
>
> In general, a good rule of thumb when designing a schema in HBase is, think
> first about how you'd ideally like to access the data. Then structure the
> data to match that access pattern. (This is obviously not ideal if you have
> lots of different access patterns, but then, that's what relational
> databases are for. Most commercial relational DBs wouldn't blink at doing
> analytical queries against 30 million rows.)
>
> Ian
>
> On Aug 25, 2011, at 9:03 AM, Rita wrote:
>
> Hello,
>
> I am trying to solve a time related problem. I can certainly use opentsdb
> for this but was wondering if anyone had a clever way to create this type
> of
> schema.
>
> I have an inventory table,
>
> time (unix epoch), fieldA, fieldB, data
>
>
> There are about 30 million of these entries.
>
> 95% of my queries will look like this:
> show me where fieldA=zCORE from range [1314180693 to now]
>
> for fieldA, there is a possibility of 4000 unique items.
> for fieldB, there is a possibility of 2 unique items (bool).
>
> So, I was thinking of creating 4000*2 tables and place the data like that
> so
> I can easly scan.
>
> Any thoughts about this? Will hbase freak out if i have 8000 tables?
>
>
>
>
>
>
> --
> --- Get your facts first, then you can distort them as you please.--
>
>
>
>
> --
> --- Get your facts first, then you can distort them as you please.--
>
>
--
--- Get your facts first, then you can distort them as you please.--
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB