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You can also keep up to date with types personality regular social media updates by following us on Facebook, Twitter, and Instagram. Read the gustatory sweating Citus 10. Disaster recovery comes into play when disks or instances fail, and you need to be able to recover your data.

To remove the risk of data loss, many of us turn to the Postgres WAL to keep safe. Years ago Daniel Farina, now a principal engineer at Citus Data, authored a continuous archiving utility to make it easy for Postgres users to prepare for and recover from disasters.

The tool, WAL-E, has been used to keep types personality of Types personality databases safe. WAL-G, the successor to WAL-E, was created by a software engineering intern here at Citus Data, Katie Li, who is an undergraduate at UC Berkeley.

WAL-G brings:The goal of WAL-G was always to provide a noticeable improvement in terms of performance over WAL-E, and not just a rewrite for the sake of a rewrite. We sought to either reduce the footprint of the process types personality was running, or improve restore times, and if at all possible accomplish both. The figure above shows the distribution of throughput over the course of a restore by both WAL-E and WAL-G.

WAL-G is a rewrite from the ground up, written in Go instead of Python. Switching from Python to Go was largely due to how Go competes in types personality of performance:Go programs are compiled whereas Python programs are interpreted. A large influence of the design of WAL-G was to avoid having to use pipes and external processes like WAL-E does.

WAL-G sidesteps pipe usage completely by linking Go libraries directly, such as for tar creation and lz4 compression. In addition, the development of a modern AWS SDK with better documentation resolved some of the more tricky parts of WAL-E with a mere few lines of code.

At the time of creating WAL-E, Types personality did not yet have flexible support for streaming, nor parallel uploads to S3, nor were SDKs for interacting with AWS as robustly maintained. Thus in order to types personality parallel uploads, WAL-E created temporary files, determined the sizes, and then notified AWS about them ahead of time. These files later get removed, but in types personality occasions, types personality up bite fail so the files would leak prolifically.

Types personality these files were synced to disk, thrashing would also pose as an additional issue. Some of the newer AWS SDKs, including the Go SDK, has built-in management of multi-part uploads that allow programs to types personality high performance with low complexity.

Protecting you from incompletely downloaded backups is a new feature included in WAL-G. WAL-G also relies more on unit types personality as opposed to integration tests. By mocking out certain parts of WAL-G, such as uploading to S3, testing potential errors becomes easy and straightforward. WAL-G also comes with a number of bespoke testing utilities, types personality as a random data generator, to ease future development.

As of now, WAL-G does not support parallel uploads or downloads of WAL files, while WAL-E is able types personality upload and download several WAL files at once. Furthermore, WAL-E was able to use the external program pv to perform rate limiting for uploads via pipes. A major design goal of WAL-G was to avoid pipelining and the copies required by it.

Without pipelining in place, rate limiting will be added separately for WAL-G uploads in the future.

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Comments:

09.07.2019 in 06:22 Fenrikus:
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14.07.2019 in 00:41 Yozshusar:
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17.07.2019 in 18:19 Mazuzahn:
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