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https://issues.apache.org/jira/browse/HBASE-4676?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13285793#comment-13285793
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Jacques commented on HBASE-4676:
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Random thought on this. I was talking to Nicolas Spiegelberg and he was
talking about how they are exploring changing encoding schemes when data
becomes more permanent. Don't quote me on this but it sounded like they were
considering using gzip compression on major compactions. I was wondering if
something similar made sense here. Basically, use less compression the shorter
the likely lifetime of files. Use the Trie compressions on only major
compactions. This way the performance difference could be less of a serious
issue since you're paying for it a fewer number of times. I glanced around and
didn't see any Jiras about a two-tiered approach of data storage formats but it
seems like that would be a prerequisite for a hybrid/tiered approach.
> Prefix Compression - Trie data block encoding
> ---------------------------------------------
>
> Key: HBASE-4676
> URL: https://issues.apache.org/jira/browse/HBASE-4676
> Project: HBase
> Issue Type: New Feature
> Components: io, performance, regionserver
> Affects Versions: 0.90.6
> Reporter: Matt Corgan
> Assignee: Matt Corgan
> Attachments: HBASE-4676-0.94-v1.patch, PrefixTrie_Format_v1.pdf,
> PrefixTrie_Performance_v1.pdf, SeeksPerSec by blockSize.png,
> hbase-prefix-trie-0.1.jar
>
>
> The HBase data block format has room for 2 significant improvements for
> applications that have high block cache hit ratios.
> First, there is no prefix compression, and the current KeyValue format is
> somewhat metadata heavy, so there can be tremendous memory bloat for many
> common data layouts, specifically those with long keys and short values.
> Second, there is no random access to KeyValues inside data blocks. This
> means that every time you double the datablock size, average seek time (or
> average cpu consumption) goes up by a factor of 2. The standard 64KB block
> size is ~10x slower for random seeks than a 4KB block size, but block sizes
> as small as 4KB cause problems elsewhere. Using block sizes of 256KB or 1MB
> or more may be more efficient from a disk access and block-cache perspective
> in many big-data applications, but doing so is infeasible from a random seek
> perspective.
> The PrefixTrie block encoding format attempts to solve both of these
> problems. Some features:
> * trie format for row key encoding completely eliminates duplicate row keys
> and encodes similar row keys into a standard trie structure which also saves
> a lot of space
> * the column family is currently stored once at the beginning of each block.
> this could easily be modified to allow multiple family names per block
> * all qualifiers in the block are stored in their own trie format which
> caters nicely to wide rows. duplicate qualifers between rows are eliminated.
> the size of this trie determines the width of the block's qualifier
> fixed-width-int
> * the minimum timestamp is stored at the beginning of the block, and deltas
> are calculated from that. the maximum delta determines the width of the
> block's timestamp fixed-width-int
> The block is structured with metadata at the beginning, then a section for
> the row trie, then the column trie, then the timestamp deltas, and then then
> all the values. Most work is done in the row trie, where every leaf node
> (corresponding to a row) contains a list of offsets/references corresponding
> to the cells in that row. Each cell is fixed-width to enable binary
> searching and is represented by [1 byte operationType, X bytes qualifier
> offset, X bytes timestamp delta offset].
> If all operation types are the same for a block, there will be zero per-cell
> overhead. Same for timestamps. Same for qualifiers when i get a chance.
> So, the compression aspect is very strong, but makes a few small sacrifices
> on VarInt size to enable faster binary searches in trie fan-out nodes.
> A more compressed but slower version might build on this by also applying
> further (suffix, etc) compression on the trie nodes at the cost of slower
> write speed. Even further compression could be obtained by using all VInts
> instead of FInts with a sacrifice on random seek speed (though not huge).
> One current drawback is the current write speed. While programmed with good
> constructs like TreeMaps, ByteBuffers, binary searches, etc, it's not
> programmed with the same level of optimization as the read path. Work will
> need to be done to optimize the data structures used for encoding and could
> probably show a 10x increase. It will still be slower than delta encoding,
> but with a much higher decode speed. I have not yet created a thorough
> benchmark for write speed nor sequential read speed.
> Though the trie is reaching a point where it is internally very efficient
> (probably within half or a quarter of its max read speed) the way that hbase
> currently uses it is far from optimal. The KeyValueScanner and related
> classes that iterate through the trie will eventually need to be smarter and
> have methods to do things like skipping to the next row of results without
> scanning every cell in between. When that is accomplished it will also allow
> much faster compactions because the full row key will not have to be compared
> as often as it is now.
> Current code is on github. The trie code is in a separate project than the
> slightly modified hbase. There is an hbase project there as well with the
> DeltaEncoding patch applied, and it builds on top of that.
> https://github.com/hotpads/hbase/tree/prefix-trie-1
> https://github.com/hotpads/hbase-prefix-trie/tree/hcell-scanners
> I'll follow up later with more implementation ideas.
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