On 01/24/2011 03:19 AM, Ben Chobot wrote:
On Jan 23, 2011, at 3:29 AM, Attila Nagy wrote:
Hello,
I'm looking for a database backend for a dictionary coder project. It would have three major tasks:
- take a text corpus, get their words and substitute each word by a 64 bit integer (the word:integer is always constant) and store the result (encoding)
- take the previous result and substitute the integers with words (decoding)
- the words should be reference counted, so if a word can be no longer found in any of the encoded messages, delete it (and optionally free it's integer ID, but 64 bit is believed to be enough for a long time, although having smaller IDs result smaller encoded files). This could be achieved by informing the database of the words of a deleted message, so it could decrement those refcounts and delete the records if needed.
Just curious, is this your end goal, or would some existing text search engine (tsearch2, lucerne, etc) fit the bill?
Yes, this isn't a text search project. Maybe data deduplication is
closer. Of course if a text search stuff fitst this, it's welcome. :)
I can easily do this with any RDBMS, with a table of three columns: auto incremented ID, word and refcount, with a unique index on word.
The challenge could be:
- that it should scale to several TBs of size and several (hundred) billion of records. One scenario would be to store about 40 TBs of words and the average word length would be about 50-60 bytes (that's about 800*10^9 records). It should work well both for inserting and searching (encoding and decoding) words.
Yes, Postgres can do this, but you're probably going to want to look into partitioning your tables. For instance, instead of a single word table, you can make word tables that store 100M words each - or if 100M ids per table doesn't sound right, pick some other number. You can still access the table as if it's a single table, and under the covers PG will use constraint exclusion to know which table partition to use.
The ID space should be continuous and unique across the tables, so a
traditional table partitioning across a key should work, but
partitioning as in sharding seems to be harder...
- I need atomicity and durability, but having these on a word (record) level takes too much IOPS and have no use, so it would be good to have an interface for inserting about 1000-500000 words in one call, assign a unique ID to each unique words and store them (if the word has had already an ID, increment its refcount) and give back the IDs for each words. This transaction could be committed as one, so the transactions could be big, sparing IOPS.
I must be something something because it's unclear why standard transactions don't give you this? Except rolling back IDs in the case of an abort, of course. Why do you need that?
Think of two documents, each of them arrive in the same time to the
encoder. If the two documents both have the word "boo", it must be given
the same ID. Giving unique constraint error for some rows of a batch
insert severely hits performance.
- I need concurrency, so when the above happens from two sources at the same time, the same word in the two transactions must get the same ID
You can't have this and the previous constraint, at least not with PG. I don't know of any system that will give you durable words but still detect when the same word is being inserted in parallel transactions, AND save you the iops of word-by-word writes.
Unless, of course, you're ok with one transaction failing due to trying to add a word that wasn't there at the start? If you did something with a unique constraint on the word, you might be able to achieve this.
I agree, this seems to be hard in a concurrent manner in a database
(maybe with a clever caching stored procedure)..
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