hbase-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Ian Varley <ivar...@salesforce.com>
Subject Re: Embedded table data model
Date Fri, 13 Jul 2012 03:08:37 GMT
Column families are not the same thing as columns. You should indeed have a small number of
column families, as that article points out. Columns (aka column qualifiers) are run-time
defined key/value pairs that contain the data for every row, and having large numbers of these
is fine. 



On Jul 12, 2012, at 7:27 PM, "Cole" <heshuai64@gmail.com> wrote:

> I think this design has some question, please refer
> http://hbase.apache.org/book/number.of.cfs.html
> 
> 2012/7/12 Ian Varley <ivarley@salesforce.com>
> 
>> 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 <ivarley@salesforce.com
>> <mailto:ivarley@salesforce.com>> 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
>> 
>> 
>> 

Mime
View raw message