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Displaying posts with tag: insert performance (reset)

MariaDB world record price per row 0.0000005$ on a single DELL R710
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Don't look at an industry benchmark here, it's a real client story.

200 Billion records in a month and it should be transactional but not durable.

For regular workload we use LOAD DATA INFILE into partitioned InnoDB, but here we have estimated 15TB of RAID storage. This is a lot of disks and it can't no more stay inside a single server internal storage.

MariaDB 5.5 come with TokuDB storage engine for compression, but is it possible in the time frame impose by the workload?

We start benchmarking 380G of raw input data files,  6 Billion rows.

First let's check the compression with the dataset.













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InnoDB scalability issues due to tables without primary keys
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Each day there is probably work done to improve performance of the InnoDB storage engine and remove bottlenecks and scalability issues. Hence there was another one I wanted to highlight:

Scalability issues due to tables without primary keys

This scalability issue is caused by the usage of tables without primary keys. This issue typically shows itself as contention on the InnoDB dict_sys mutex. Now the dict_sys mutex controls access to the data dictionary. This mutex is used at various places. I will only mention a few of them:

  • During operations such as opening and closing table handles, or
  • When accessing I_S tables, or
  • During undo of a freshly inserted row, or
  • During other data dictionary modification operations such as CREATE TABLE, or
  • Within the “Persistent Stats” subsystem,
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Benchmarking single-row insert performance on Amazon EC2
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I have been working for a customer benchmarking insert performance on Amazon EC2, and I have some interesting results that I wanted to share. I used a nice and effective tool iiBench which has been developed by Tokutek. Though the “1 billion row insert challenge” for which this tool was originally built is long over, but still the tool serves well for benchmark purposes.

OK, let’s start off with the configuration details.

Configuration

First of all let me describe the EC2 instance type that I used.

EC2 Configuration

I chose m2.4xlarge instance as that’s the instance type with highest memory available, and memory is what really really matters.

High-Memory Quadruple Extra Large
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