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" <[email protected]> wrote: > I think this design has some question, please refer > http://hbase.apache.org/book/number.of.cfs.html > > 2012/7/12 Ian Varley <[email protected]> > >> 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 >> >> >>
