Posted by: shaik abdul ghouse ahmed Date: February 04, 2010 05:53AM Hi, Hi, We have an appliction, java based, web based gateway, with backend as mssql, It is for a manufacturing application, with 150+ real time data points to be logged every second. Storage. But as the metadata grew rapidly, standalone MySQL couldn't meet our storage requirements. There are about 30M seconds in a year; 86,400 seconds per day. I say legacy, but I really mean a prematurely-optimized system that I’d like to make less smart. Now, I hope anyone with a million-row table is not feeling bad. Right now there are approximately 12 million rows in the location table, and things are getting slow now, as a full table scan can take ~3-4 minutes on my limited hardware. Posted by: daofeng luo Date: November 26, 2004 01:13AM Hi, I am a web adminstrator. MYSQL and 4 Billion Rows. Even Faster: Loading Half a Billion Rows in MySQL Revisited A few months ago, I wrote a post on loading 500 million rows into a single innoDB table from flatfiles. Previously, we used MySQL to store OSS metadata. Every time someone would hit a button to view audit logs in our application, our mysql service would have to churn through 1billion rows on a single large table. On the disk, it amounted to about half a terabyte. In my case, I was dealing with two very large tables: one with 1.4 billion rows and another with 500 million rows, plus some other smaller tables with a few hundreds of thousands of rows each. Then we adopted the solution of MySQL sharding and Master High Availability Manager , but this solution was undesirable when 100 billion new records flooded into our database each month. For all the same reasons why a million rows isn’t very much data for a regular table, a million rows also isn’t very much for a partition in a partitioned table. You can still use them quite well as part of big data analytics, just in the appropriate context. Let us first create a table− mysql> create table DemoTable ( Value BIGINT ); Query OK, 0 rows affected (0.74 sec) Look at your data; compute raw rows per second. Several possibilities come to mind: 1) indexing strategy 2) efficient queries 3) resource configuration 4) database design First - Perhaps your indexing strategy can be improved. Before using TiDB, we managed our business data on standalone MySQL. I currently have a table with 15 million rows. Each "location" entry is stored as a single row in a table. Loading half a billion rows into MySQL Background. From your experience, what's the upper limit of rows in a MyISAM table can MySQL handle efficiently on a server with Q9650 CPU (4-core, 3.0G) and 8G RAM. 10 rows per second is about all you can expect from an ordinary machine (after allowing for various overheads). Requests to view audit logs would… We have a legacy system in our production environment that keeps track of when a user takes an action on Causes.com (joins a Cause, recruits a friend, etc). In the future, we expect to hit 100 billion or even 1 trillion rows. You can use FORMAT() from MySQL to convert numbers to millions and billions format. A user's phone sends its location to the server and it is stored in a MySQL database. I received about 100 million visiting logs everyday. It's pretty fast. can mysql table exceed 42 billion rows? I store the logs in 10 tables per day, and create merge table on log tables when needed. Inserting 30 rows per second becomes a billion rows per year. If the scale increases to 1 billion rows, do I need to partition it into 10 tables with 100 million rows … As data volume surged, the standalone MySQL system wasn't enough. We faced severe challenges in storing unprecedented amounts of data that kept soaring. 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