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From Michael Segel <mse...@segel.com>
Subject Re: data partitioning and data model
Date Mon, 23 Feb 2015 20:34:59 GMT

Yes you would want to start your key by user_id. 
But you don’t need the timestamp. The user_id + alert_id should be enough on the key. 
If you want to get fancy…

If your alert_id is not a number, you could use the EPOCH - Timestamp as a way to invert the
order of the alerts so that the latest alert would be first.
If your alert_id is a number  you could just use EPOCH - alert_id to get the alerts in reverse
order with the latest alert first. 

Depending on the number of alerts, you could make the table wider and store multiple alerts
in a row… but that brings in a different debate when it comes to row width and how you use
the data. 

> On Feb 20, 2015, at 12:55 PM, Alok Singh <aloksingh@gmail.com> wrote:
> You can use a key like (user_id + timestamp + alert_id) to get
> clustering of rows related to a user. To get better write throughput
> and distribution over the cluster, you could pre-split the table and
> use a consistent hash of the user_id as a row key prefix.
> Have you looked at the rowkey design section in the hbase book :
> http://hbase.apache.org/book.html#rowkey.design
> Alok
> On Fri, Feb 20, 2015 at 8:49 AM, Marcelo Valle (BLOOMBERG/ LONDON)
> <mvallemilita@bloomberg.net> wrote:
>> Hello,
>> This is my first message in this mailing list, I just subscribed.
>> I have been using Cassandra for the last few years and now I am trying to create
a POC using HBase. Therefore, I am reading the HBase docs but it's been really hard to find
how HBase behaves in some situations, when compared to Cassandra. I thought maybe it was a
good idea to ask here, as people in this list might know the differences better than anyone
>> What I want to do is creating a simple application optimized for writes (not interested
in HBase / Cassandra product comparisions here, I am assuming I will use HBase and that's
it, just wanna understand the best way of doing it in HBase world). I want to be able to write
alerts to the cluster, where each alert would have columns like:
>> - alert id
>> - user id
>> - date/time
>> - alert data
>> Later, I want to search for alerts per user, so my main query could be considered
to be something like:
>> Select * from alerts where user_id = $id and date/time > 10 days ago.
>> I want to decide the data model for my application.
>> Here are my questions:
>> - In Cassandra, I would partition by user + day, as some users can have many alerts
and some just 1 or a few. In hbase, assuming all alerts for a user would always fit in a single
partition / region, can I just use user_id as my row key and assume data will be distributed
along the cluster?
>> - Suppose I want to write 100 000 rows from a client machine and these are from 30
000 users. What's the best manner to write these if I want to optimize for writes? Should
I batch all 100 k requests in one to a single server? As I am trying to optimize for writes,
I would like to split these requests across several nodes instead of sending them all to one.
I found this article: http://hortonworks.com/blog/apache-hbase-region-splitting-and-merging/
But not sure if it's what I need
>> Thanks in advance!
>> Best regards,
>> Marcelo.

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