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. 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. Let us first create a table− mysql> create table DemoTable ( Value BIGINT ); Query OK, 0 rows affected (0.74 sec) can mysql table exceed 42 billion rows? Previously, we used MySQL to store OSS metadata. Each "location" entry is stored as a single row in a table. I received about 100 million visiting logs everyday. But as the metadata grew rapidly, standalone MySQL couldn't meet our storage requirements. 10 rows per second is about all you can expect from an ordinary machine (after allowing for various overheads). As data volume surged, the standalone MySQL system wasn't enough. 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). 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. We faced severe challenges in storing unprecedented amounts of data that kept soaring. 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. 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. Requests to view audit logs would… I say legacy, but I really mean a prematurely-optimized system that I’d like to make less smart. There are about 30M seconds in a year; 86,400 seconds per day. 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. 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. Look at your data; compute raw rows per second. Now, I hope anyone with a million-row table is not feeling bad. Storage. MYSQL and 4 Billion Rows. I currently have a table with 15 million rows. You can use FORMAT() from MySQL to convert numbers to millions and billions format. In the future, we expect to hit 100 billion or even 1 trillion rows. You can still use them quite well as part of big data analytics, just in the appropriate context. It's pretty fast. 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. On the disk, it amounted to about half a terabyte. Inserting 30 rows per second becomes a billion rows per year. 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. Loading half a billion rows into MySQL Background. If the scale increases to 1 billion rows, do I need to partition it into 10 tables with 100 million rows … I store the logs in 10 tables per day, and create merge table on log tables when needed. Before using TiDB, we managed our business data on standalone MySQL. Posted by: daofeng luo Date: November 26, 2004 01:13AM Hi, I am a web adminstrator. A user's phone sends its location to the server and it is stored in a MySQL database. 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