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From Andrey Stepachev <oct...@gmail.com>
Subject Re: Insert into tall table 50% faster than wide table
Date Thu, 23 Dec 2010 07:14:18 GMT
I think row locks slows down here. Each row you inserted tries to aquire
lock, and then release it. Wide table has significally less rows, and much
less locks acquired during insert.


2010/12/23 Bryan Keller <bryanck@gmail.com>

> 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?
>
>

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