Load Files from Amazon S3 and HDFS with the SingleStore Loader

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Dec 30, 2014

Load Files from Amazon S3 and HDFS with the SingleStore Loader

One of the most common tasks with any database is loading large amounts of data into it from an external data store. Both SingleStore and MySQL provide the LOAD DATA command for this task; this command is very powerful, but by itself, it has a number of restrictions:

  • It can only read from the local filesystem, so loading data from a remote store like Amazon S3 requires first downloading the files you need.

  • Since it can only read from a single file at a time, loading from multiple files requires multiple LOAD DATA commands. If you want to perform this work in parallel, you have to write your own scripts.

  • If you are loading multiple files, it’s up to you to make sure that you’ve deduplicated the files and their contents.

why-we-built-the-single-store-loaderWhy We Built the SingleStore Loader

At SingleStore, we’ve acutely felt all of these limitations. That’s why we developed SingleStore Loader, which solves all of the above problems and more. SingleStore Loader lets you load files from Amazon S3, the Hadoop Distributed File System (HDFS), and the local filesystem. You can specify all of the files you want to load with one command, and SingleStore Loader will take care of deduplicating files, parallelizing the workload, retrying files if they fail to load, and more.

Use a load command to load a set of files

View the progress of a job using the ps command

We have been using SingleStore Loader here at SingleStore for quite a while now, and have provided a binary version on our website for anyone to use. However, we are proud of the code we produced (or at least proud enough), and have decided to open source the SingleStore Loader project.

Give SingleStore Loader a Try – Download Now on GitHub

The project uses several open source libraries, such as the Voluptuous data validation library and our own SingleStore Python connector. You can find the project here. Check it out, and let us know what you think!


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