Perhaps slow wide table insert performance is related to row versioning? If I have a customer row and keep adding order columns one by one, I'm thinking that there might be a version kept of the row for every order I add? If I am simply inserting a new row for every order, there is no versioning going on. Could this be causing performance problems?
On Dec 22, 2010, at 4:16 PM, Bryan Keller wrote: > It appears to be the same or better, not to derail my original question. The > much slower write performance will cause problems for me unless I can resolve > that. > > On Dec 22, 2010, at 3:52 PM, Peter Haidinyak wrote: > >> Interesting, do you know what the time difference would be on the other >> side, doing a lookup/scan? >> >> Thanks >> >> -Pete >> >> -----Original Message----- >> From: Bryan Keller [mailto:[email protected]] >> Sent: Wednesday, December 22, 2010 3:41 PM >> To: [email protected] >> Subject: Insert into tall table 50% faster than wide table >> >> I have been testing a couple of different approaches to storing customer >> orders. One is a tall table, where each order is a row. The other is a wide >> table where each customer is a row, and orders are columns in the row. I am >> finding that inserts into the tall table, i.e. adding rows for every order, >> is roughly 50% faster than inserts into the wide table, i.e. adding a row >> for a customer and then adding columns for orders. >> >> In my test, there are 10,000 customers, each customer has 600 orders and >> each order has 10 columns. The tall table approach results in 6 mil rows of >> 10 columns. The wide table approach results is 10,000 rows of 6,000 columns. >> I'm using hbase 0.89-20100924 and hadoop 0.20.2. I am adding the orders >> using a Put for each order, submitted in batches of 1000 as a list of Puts. >> >> Are there techniques to speed up inserts with the wide table approach that I >> am perhaps overlooking? >> >
