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