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HBase >> mail # user >> Embedded table data model


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Re: Embedded table data model
Yes, that's fine; you can always do a single column PUT into an existing row, in a concurrency-safe way, and the lock on the row is only held as long as it takes to do that. Because of HBase's Log-Structured Merge-Tree architecture, that's efficient because the PUT only goes to memory, and is merged with on-disk records at read time (until a regular flush or compaction happens).

So even though you already have, say, 10K transactions in the table, it's still efficient to PUT a single new transaction in (whether that's in the middle of the sorted list of columns, at the end, etc.)

Ian

On Jul 11, 2012, at 11:27 PM, Xiaobo Gu wrote:

but they are other writers insert new transactions into the table when
customers do new transactions.

On Thu, Jul 12, 2012 at 1:13 PM, Ian Varley <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>> wrote:
Hi Xiaobo -

For HBase, this is doable; you could have a single table in HBase where each row is a customer (with the customerid as the rowkey), and columns for each of the 300 attributes that are directly part of the customer entity. This is sparse, so you'd only take up space for the attributes that actually exist for each customer.

You could then have (possibly in another column family, but not necessarily) an additional column for each transaction, where the column name is composed of a date concatenated with the transaction id, in which you store the 30 attributes as serialized into a single byte array in the cell value. (Or, you could alternately do each attribute as its own column but there's no advantage to doing so, since presumably a transaction is roughly like an immutable event that you wouldn't typically change just a single attribute of.) A schema for this (if spelled out in an xml representation) could be:

<table name="customer">
 <key>
   <column name="customerid">
 </key>
 <columnfamily name="1">
   <column name="customer_attribute_1" />
   <column name="customer_attribute_2" />
   ...
   <column name="customer_attribute_300" />
 </columnFamily>
 <columnFamily name="2">
   <entity name="transaction" values="serialized">
     <key>
       <column name="transaction_date" type="date">
       <column name="transaction_id" />
     </key>
     <column name="transaction_attribute_1" />
     <column name="transaction_attribute_2" />
     ...
     <column name="transaction_attribute_30" />
   </entity>
 </columnFamily>
</table>

(This isn't real HBase syntax, it's just an abstract way to show you the structure.) In practice, HBase isn't doing anything "special" with the entity that lives nested inside your table; it's just a matter of convention, that you could "see" it that way. The customer-level attributes (like, say, "customer_name" and "customer_address") would be literal column names (aka column qualifiers) embedded in your code, whereas the transaction-oriented columns would be created at runtime with column names like "2012-07-11 12:34:56_TXN12345", and values that are simply collection objects (containing the 30 attributes) serialized into a byte array.

In this scenario, you get fast access to any customer by ID, and further to a range of transactions by date (using, say, a column pagination filter). This would perform roughly equivalently regardless of how many customers are in the table, or how many transactions exist for each customer. What you'd lose on this design would be the ability to get a single transaction for a single customer by ID (since you're storing them by date). But if you need that, you could actually store it both ways. You also might be introducing some extra contention on concurrent transaction PUT requests for a single client, because they'd have to fight over a lock for the row (but that's probably not a big deal, since it's only contentious within each customer).

You might find my presentation on designing HBase schemas (from this year's HBaseCon) useful:

http://www.hbasecon.com/sessions/hbase-schema-design-2/

Ian

On Jul 11, 2012, at 10:58 PM, Xiaobo Gu wrote:

Hi,

I have technical problem, and wander whether HBase or Cassandra
support Embedded table data model, or can somebody show me a way to do
this:

1.We have a very large customer entity table which have 100 milliion
rows, each customer row has about 300 attributes(columns).
2.Each customer do about 1000 transactions per year, each transaction
has about 30 attributes(columns), and we just save one year
transactions for each customer

We want a data model that  we can get the customer entity with all the
transactions which he did for a single client call within a fixed time
window, according to the customer id (which is the primary key of the
customer table). We do the following in RDBMS,
A customer table with customerid as the primary key, A transaction
table with customer id as a secondary index, and join them , or we
must do two separate  calls, and because we have so many concurrent
readers and these two tables are became so large, the RDBMS system
performs poor.
Can we embedded the transactions inside the customer table in HBase or
Cassandra?
Regards,

Xiaobo Gu
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