Home > Enterprise >  Running into some SQLite limitation using IN operator
Running into some SQLite limitation using IN operator

Time:10-26

I have a query that uses WHERE id IN (1,2,3,...) where the list (1,2,3,...) is dynamically generated from an array of integers (not using parameters). Now I have a particular query that takes roughly 500ms with 26623 ids but 50s (100x slower) with 26624 ids.

I couldn't find anything that looks related in https://sqlite.org/limits.html

SELECT params.name AS name, json_group_array(DISTINCT params.value) AS "values"
FROM view_requests AS req, search_params(search) AS params
JOIN flows ON flows.request_id = req.id
WHERE search NOT IN ('', '?')
AND flows.id IN (1,2,3) /* <=== here more than 26623 IDs make it super slow  */
GROUP BY params.name
ORDER BY json_array_length("values") DESC, params.name ASC

Before I try to make that reproducible in isolate (e.g. search_params is a custom virtual table), does anyone know what limitation I might be running into? It's not the number of IDs per se, since a different query runs just fine with the same IDs.

SQLite version 3.36.0 via better-sqlite3 (Node.js) with a readonly database. The only pragma I use is journal_mode = WAL.

Compiled with (https://github.com/JoshuaWise/better-sqlite3/blob/master/docs/compilation.md#bundled-configuration):

SQLITE_DQS=0
SQLITE_LIKE_DOESNT_MATCH_BLOBS
SQLITE_THREADSAFE=2
SQLITE_USE_URI=0
SQLITE_DEFAULT_MEMSTATUS=0
SQLITE_OMIT_DEPRECATED
SQLITE_OMIT_GET_TABLE
SQLITE_OMIT_TCL_VARIABLE
SQLITE_OMIT_PROGRESS_CALLBACK
SQLITE_OMIT_SHARED_CACHE
SQLITE_TRACE_SIZE_LIMIT=32
SQLITE_DEFAULT_CACHE_SIZE=-16000
SQLITE_DEFAULT_FOREIGN_KEYS=1
SQLITE_DEFAULT_WAL_SYNCHRONOUS=1
SQLITE_ENABLE_MATH_FUNCTIONS
SQLITE_ENABLE_DESERIALIZE
SQLITE_ENABLE_COLUMN_METADATA
SQLITE_ENABLE_UPDATE_DELETE_LIMIT
SQLITE_ENABLE_STAT4
SQLITE_ENABLE_FTS3_PARENTHESIS
SQLITE_ENABLE_FTS3
SQLITE_ENABLE_FTS4
SQLITE_ENABLE_FTS5
SQLITE_ENABLE_JSON1
SQLITE_ENABLE_RTREE
SQLITE_ENABLE_GEOPOLY
SQLITE_INTROSPECTION_PRAGMAS
SQLITE_SOUNDEX
HAVE_STDINT_H=1
HAVE_INT8_T=1
HAVE_INT16_T=1
HAVE_INT32_T=1
HAVE_UINT8_T=1
HAVE_UINT16_T=1
HAVE_UINT32_T=1

CodePudding user response:

Here's the answer from the SQLite forums. Essentially this is a combination of how the query planner handles IN literals and what cost my virtual table estimates. That means I'm running into the exact moment when the query planner makes a different decision.

SQLite NGQP is a cost based query planner. The IN () operator with a list of literal values gets implemented as a kind of temporary table; sometimes SQLite decides to create an index and do lookups, other times it decides to use that table as the outermost loop of the query.

EXPLAIN QUERY PLAN should show that in a more concise manner.

If compiled in DEBUG mode mith WHERETRACE enabled, the .wheretrace command will show how SQLite NGQP reaches its plan. Essential input is the return values from the xBestIndex method of your virtual table, especially the "number of rows" and the "estimated cost". It is paramount to deliver accurate estimates. Cost should reflect processing cost relative to SQLite native tables.

Note that you can name the IN table by making it a CTE and CROSS JOIN to force the query plan that works fast.

https://sqlite.org/forum/forumpost/a3d68ed8b40cf583?t=h

The workaround I use is json_each and serialize the array of integers into a JSON string. In my particular use-case this has some other benefits as well (e.g. I can bind a single parameter and re-use the query with any number of IDs), so I don't mind doing that:

 SELECT params.name AS name, json_group_array(DISTINCT params.value) AS "values"
 FROM view_requests AS req, search_params(search) AS params
 JOIN flows ON flows.request_id = req.id
 WHERE search NOT IN ('', '?')
-AND flows.id IN (1,2,3)
 AND flows.id IN (SELECT value FROM json_each('[1,2,3]'))
 GROUP BY params.name
 ORDER BY json_array_length("values") DESC, params.name ASC

I also know that the generic virtual table implementation of better-sqlite3 makes a trade-off between being easy to use (it's ridiculously easy) and achieving maximum performance.

  • Related