S3 Engine Internals
Learn about the internal architecture of the S3 engine, which inherits from Aria code but redirects reads to S3, using a dedicated page cache.
The S3 storage engine is based on the Aria code. Internally, the S3 storage inherits from the Aria code, with hooks that change reads, so that instead of reading data from the local disk it reads things from S3.
The S3 engine uses it's own page cache, modified to be able to handle reading blocks from S3 (of size s3_block_size). Internally the S3 page cache uses pages of aria-block-size for splitting the blocks read from S3.
ALTER TABLE
ALTER TABLE will first create a local table in the normal Aria on disk format and then move both index and data to S3 in buckets of S3_BLOCK_SIZE. The .frm file is also copied to S3 for discovery to support discovery for other MariaDB servers. You can also use ALTER TABLE to change the structure of an S3 table.
Partitioning Tables
S3 tables can also be used with Partitioning tables. All ALTER PARTITION operations are supported except:
REBUILD PARTITIONTRUNCATE PARTITIONREORGANIZE PARTITION
Big Reads
One of the properties of many S3 implementations is that they favor large reads. It's said that 4M gives the best performance, which is why the default value for S3_BLOCK_SIZE is 4M.
Compression
If compression (COMPRESSION_ALGORITHM=zlib) is used, then all index blocks and data blocks are compressed. The .frm file and Aria definition header (first page/pages in the index file) are not compressed as these are used by discovery/open.
If compression is used, then the local block size is S3_BLOCK_SIZE, but the block stored in S3 are the size of the compressed block.
Typical compression we have seen is in the range of 80% saved space.
Structure Stored on S3
The table are copied in S3 into the following locations:
block_number is a 6-digit decimal number, prefixed with 0. (It can be larger than 6 numbers – the prefix is just for nice output.)
Using the awsctl Python Tool to Examine Data
Installing awsctl on Linux
Using the awsctl Tool
One can use the aws python tool to see how things are stored on S3:
To delete an obsolete table foo.test1 one can do:
See Also
This page is licensed: CC BY-SA / Gnu FDL
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