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From "Paul Joseph Davis (JIRA)" <j...@apache.org>
Subject [jira] Commented: (COUCHDB-1092) Storing documents bodies as raw JSON binaries instead of serialized JSON terms
Date Thu, 17 Mar 2011 14:54:30 GMT

    [ https://issues.apache.org/jira/browse/COUCHDB-1092?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13007937#comment-13007937
] 

Paul Joseph Davis commented on COUCHDB-1092:
--------------------------------------------

@Filipe

> I think you're being overpicky. 

Perhaps.

> However you're adding about 300 lines to do exactly the same.

This is nowhere close to "exactly the same". My solution guarantees correct JSON bodies are
output regardless of who or what calls these functions. The other version is why SQL injections
exist.

json_stream_parse.erl is 432 lines. Why don't we get rid of that and just do some byte scanning?

> But it adds more overhead, as it scans every single byte of the document body in the
end (validate_object function) to check it's valid.

Yep, its basically a full JSON parse except it doesn't create terms and does the splicing
stuff.


The bigger question here is whether we've suddenly stopped prioritizing correctness above
all other concerns. Feel free to vote on a version that doesn't include some method of validation
in couch_doc.erl just know that I'd -1 it for that exact reason. We can't just create a core
API that doesn't sanitize outputs, that's just crazy talk.



> Storing documents bodies as raw JSON binaries instead of serialized JSON terms
> ------------------------------------------------------------------------------
>
>                 Key: COUCHDB-1092
>                 URL: https://issues.apache.org/jira/browse/COUCHDB-1092
>             Project: CouchDB
>          Issue Type: Improvement
>          Components: Database Core
>            Reporter: Filipe Manana
>            Assignee: Filipe Manana
>
> Currently we store documents as Erlang serialized (via the term_to_binary/1 BIF) EJSON.
> The proposed patch changes the database file format so that instead of storing serialized
> EJSON document bodies, it stores raw JSON binaries.
> The github branch is at:  https://github.com/fdmanana/couchdb/tree/raw_json_docs
> Advantages:
> * what we write to disk is much smaller - a raw JSON binary can easily get up to 50%
smaller
>   (at least according to the tests I did)
> * when serving documents to a client we no longer need to JSON encode the document body
>   read from the disk - this applies to individual document requests, view queries with
>   ?include_docs=true, pull and push replications, and possibly other use cases.
>   We just grab its body and prepend the _id, _rev and all the necessary metadata fields
>   (this is via simple Erlang binary operations)
> * we avoid the EJSON term copying between request handlers and the db updater processes,
>   between the work queues and the view updater process, between replicator processes,
etc
> * before sending a document to the JavaScript view server, we no longer need to convert
it
>   from EJSON to JSON
> The changes done to the document write workflow are minimalist - after JSON decoding
the
> document's JSON into EJSON and removing the metadata top level fields (_id, _rev, etc),
it
> JSON encodes the resulting EJSON body into a binary - this consumes CPU of course but
it
> brings 2 advantages:
> 1) we avoid the EJSON copy between the request process and the database updater process
-
>    for any realistic document size (4kb or more) this can be very expensive, specially
>    when there are many nested structures (lists inside objects inside lists, etc)
> 2) before writing anything to the file, we do a term_to_binary([Len, Md5, TheThingToWrite])
>    and then write the result to the file. A term_to_binary call with a binary as the
input
>    is very fast compared to a term_to_binary call with EJSON as input (or some other
nested
>    structure)
> I think both compensate the JSON encoding after the separation of meta data fields and
non-meta data fields.
> The following relaximation graph, for documents with sizes of 4Kb, shows a significant
> performance increase both for writes and reads - especially reads.   
> http://graphs.mikeal.couchone.com/#/graph/698bf36b6c64dbd19aa2bef63400b94f
> I've also made a few tests to see how much the improvement is when querying a view, for
the
> first time, without ?stale=ok. The size difference of the databases (after compaction)
is
> also very significant - this change can reduce the size at least 50% in common cases.
> The test databases were created in an instance built from that experimental branch.
> Then they were replicated into a CouchDB instance built from the current trunk.
> At the end both databases were compacted (to fairly compare their final sizes).
> The databases contain the following view:
> {
>     "_id": "_design/test",
>     "language": "javascript",
>     "views": {
>         "simple": {
>             "map": "function(doc) { emit(doc.float1, doc.strings[1]); }"
>         }
>     }
> }
> ## Database with 500 000 docs of 2.5Kb each
> Document template is at:  https://github.com/fdmanana/couchdb/blob/raw_json_docs/doc_2_5k.json
> Sizes (branch vs trunk):
> $ du -m couchdb/tmp/lib/disk_json_test.couch 
> 1996	couchdb/tmp/lib/disk_json_test.couch
> $ du -m couchdb-trunk/tmp/lib/disk_ejson_test.couch 
> 2693	couchdb-trunk/tmp/lib/disk_ejson_test.couch
> Time, from a user's perpective, to build the view index from scratch:
> $ time curl http://localhost:5984/disk_json_test/_design/test/_view/simple?limit=1
> {"total_rows":500000,"offset":0,"rows":[
> {"id":"0000076a-c1ae-4999-b508-c03f4d0620c5","key":null,"value":"wfxuF3N8XEK6"}
> ]}
> real	6m6.740s
> user	0m0.016s
> sys	0m0.008s
> $ time curl http://localhost:5985/disk_ejson_test/_design/test/_view/simple?limit=1
> {"total_rows":500000,"offset":0,"rows":[
> {"id":"0000076a-c1ae-4999-b508-c03f4d0620c5","key":null,"value":"wfxuF3N8XEK6"}
> ]}
> real	15m41.439s
> user	0m0.012s
> sys	0m0.012s
> ## Database with 100 000 docs of 11Kb each
> Document template is at:  https://github.com/fdmanana/couchdb/blob/raw_json_docs/doc_11k.json
> Sizes (branch vs trunk):
> $ du -m couchdb/tmp/lib/disk_json_test_11kb.couch
> 1185	couchdb/tmp/lib/disk_json_test_11kb.couch
> $ du -m couchdb-trunk/tmp/lib/disk_ejson_test_11kb.couch
> 2202	couchdb-trunk/tmp/lib/disk_ejson_test_11kb.couch
> Time, from a user's perpective, to build the view index from scratch:
> $ time curl http://localhost:5984/disk_json_test_11kb/_design/test/_view/simple?limit=1
> {"total_rows":100000,"offset":0,"rows":[
> {"id":"00001511-831c-41ff-9753-02861bff73b3","key":null,"value":"2fQUbzRUax4A"}
> ]}
> real	4m19.306s
> user	0m0.008s
> sys	0m0.004s
> $ time curl http://localhost:5985/disk_ejson_test_11kb/_design/test/_view/simple?limit=1
> {"total_rows":100000,"offset":0,"rows":[
> {"id":"00001511-831c-41ff-9753-02861bff73b3","key":null,"value":"2fQUbzRUax4A"}
> ]}
> real	18m46.051s
> user	0m0.008s
> sys	0m0.016s
> All in all, I haven't seen yet any disadvantage with this approach. Also, the code changes
> don't bring additional complexity. I say the performance and disk space gains it gives
are
> very positive.
> This branch still needs to be polished in a few places. But I think it isn't far from
getting mature.
> Other experiments that can be done are to store view values as raw JSON binaries as well
(instead of EJSON)
> and optional compression of the stored JSON binaries (since it's pure text, the compression
ratio is very high).
> However, I would prefer to do these other 2 suggestions in separate branches/patches
- I haven't actually tested
> any of them yet, so maybe they not bring significant gains.
> Thoughts? :)

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