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HBase >> mail # user >> Row Key Design in time based aplication


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Mehmet Simsek 2013-02-17, 19:33
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James Taylor 2013-02-17, 22:50
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Re: Row Key Design in time based aplication
I'm not sure how a SQL interface above HBase will solve some of the issues with regional hot spotting when using time as the key. Or the problem with always adding data to the right of the last row.

The same would apply with the project id, assuming that it too is a number that grows incrementally with each project.
On Feb 17, 2013, at 4:50 PM, James Taylor <[EMAIL PROTECTED]> wrote:

> Hello,
> Have you considered using Phoenix (https://github.com/forcedotcom/phoenix) for this use case? Phoenix is a SQL layer on top of HBase. For this use case, you'd connect to your cluster like this:
>
> Class.forName("com.salesforce.phoenix.jdbc.PhoenixDriver"); // register driver
> Connection conn = DriverManager..getConnection("jdbc:phoenix:localhost"); // connect to local HBase
>
> Create a table like this (adding additional columns that you want to measure, like txn_count below):
>
> conn.createStatement().execute(
>    "CREATE TABLE event_log (\n" +
>    "     project_id INTEGER NOT NULL, \n" +
>    "    time DATE NOT NULL,\n" +
>    "txn_count LONG\n" +
>    "CONSTRAINT pk PRIMARY KEY (project_id, time))");
>
> Then to insert data you'd do this:
>
> PreparedStatement preparedStmt = conn.prepareStatement(
>    "UPSERT INTO event_log VALUES(?,?,0)");
>
> and you'd bind the values in JDBC like this:
>
> preparedStmt.setInt(1, projectId);
> preparedStmt.setDate(2, time);
> preparedStmt.execute();
>
> conn.commit(); // If upserting many values, you'd want to commit after upserting maybe 1000-10000 rows
>
> Then at query data time, assuming you want to report on this data by grouping into different "time buckets", you could do as show below. Phoenix stores your date values at the millisecond granularity and you can decide a query time how you'd like to roll it up:
>
> // Query with time bucket at the hour granularity
> conn.createStatement().execute(
>   "SELECT\n" +
>   "    project_id, TRUNC(time,'HOUR') as time_bucket, \n" +
>   "    MIN(txnCount), MAX(txnCount), AVG(txnCount) FROM event_log\n" +
>   "GROUP BY project_id, TRUNC(time,'HOUR')");
>
> // Query with time bucket at the day granularity
> conn.createStatement().execute(
>    "SELECT\n" +
>    "    project_id, TRUNC(time,'DAY') as time_bucket,\n" +
>    "    MIN(txnCount), MAX(txnCount), AVG(txnCount) FROM event_log\n" +
>    "GROUP BY project_id, TRUNC(time,'DAY')");
>
> You could, of course include a WHERE clause in the query to filter based on the range of dates, particular projectIds, etc. like this:
>
> conn.prepareStatement(
>    "SELECT\n" +
>    "    project_id, TRUNC(time,'DAY') as time_bucket,\n" +
>    "    MIN(txnCount), MAX(txnCount), AVG(txnCount) FROM event_log\n" +
>    "WHERE project_id IN (?, ?, ?) AND date >= ? AND date < ?\n" +
>    "GROUP BY project_id, TRUNC(time,'DAY')");
> preparedStmt.setInt(1, projectId1);
> preparedStmt.setInt(2, projectId2);
> preparedStmt.setInt(3, projectId3);
> preparedStmt.setDate(4, beginDate);
> preparedStmt.setDate(5, endDate);
> preparedStmt.execute();
>
>
> HTH.
>
> Regards,
>
>    James
>
> On 02/17/2013 11:33 AM, Mehmet Simsek wrote:
>> Hi,
>>
>> I want to hold event log data in hbase but I couldn't decide row key. I must hold project id and time,I will use project ld and time combination while searching.
>>
>> Row key can be below
>>
>> ProjectId+timeInMs
>>
>> In similiar application(open source TSDB) time is divided 1000 to round in this project.I can use this strategy but I don't know how we decide what divider must be?  1000 or 10000.
>>
>> Why time is divided 1000 in this application? why didn't be hold without division?
>>
>> Can you explain this strategy?
>>
>
>

Michael Segel  | (m) 312.755.9623

Segel and Associates
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Mohammad Tariq 2013-02-17, 23:30
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James Taylor 2013-02-18, 01:19
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Michael Segel 2013-02-18, 01:29
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Asaf Mesika 2013-02-21, 22:49
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