I would greatly appreciate any advice anyone could give me in terms of performance tuning a large PL/PGSQL stored procedure. First, I should point out that I have read a considerable amount of information in the online PostgreSQL documentation and on Google about optimizing SQL queries and PostgreSQL. I am looking for any additional insights that my research may have overlooked. So, let me explain a little about how this stored procedure is constructed.
The stored procedure is written in PL/PGSQL and is 3,000+ lines long. It works with around 60 tables and a dozen or so complex types that are defined in an additional 2,000 lines of SQL.
The procedure takes individual arguments of various types as input parameters and returns a single row result of a complex type.
The complex type contains roughly 25 fields, mostly text, plus another 10 REFCURSORs.
The application that calls the stored procedure was also written by me in C++ and uses asynchronous libpq API commands to execute a single SQL transaction which calls the stored procedure and also performs a FETCH ALL on all open cursors. It then returns all results into various structures. All rows of all cursors that are open are always used for every call to the stored procedure.
The stored procedure implements various logic which determines which tables in the database to query and how to filter the results from those queries to return only the relevant information needed by the C++ application.
Currently, in terms of optimization, I have taken the following approaches based on the following reasoning:
1. For all queries whose results need to return to the C++ application, I utilize cursors so that all results can be readied and generated by the stored procedure with just one call to the PostgreSQL backend. I accomplish this using asynchronous libpq API calls to issue a single transaction to the server. The first command after the BEGIN is a SELECT * FROM MyStoredProc(blah), which is then followed by FETCH ALL commands for each cursor that the stored procedure leaves open. I then follow up with multiple API calls to return the results and retrieve the rows from those results. This minimizes the amount of back-and-forth between my C++ application and the database backend.
1a. Incidentally, I am also using cursors for most queries inside the stored procedure that do not return results to the C++ application. I am unsure whether this incurs a performance penalty compared to doing, for example, a SELECT ... INTO (var1, var2, ...) within the body of the stored procedure. Instead of using SELECT ... INTO, I am using OPEN cursor_name; FETCH cursor_name INTO (var1, var2).
2. I have built indexes on all columns that are used in where clauses and joins.
3. I use lots of joins to pull in data from various tables (there are around 60 tables that are queried with each call to the stored procedure).
4. When performing joins, the first table listed is the one that returns the most context-specific results, which always also means that it has the most-specific and fewest number of relevant rows. I then join them in order of least number of result rows with all inner joins preceding left outer joins.
5. Instead of using UNIONs and EXCEPT clauses, I use multiple WITH clauses to define several different query-specific views. I order them such that I can join additional tables in later WITH clauses to the views created previously in a way that minimizes the number of rows involved in the JOIN operations while still providing provably accurate result sets. The EXCEPT clauses are then replaced by also defining one view which contains a set of IDs that I want filtered from the final result set and using a WHERE id NOT IN (SELECT id FROM filtered_view). Typically, this approach leaves me with just one UNION of two previously defined views (the union is required because it is returning results from different tables with different columns), which is then aliased and joined to additional tables. This allows all of the the JOINS and the sole remaining UNION to be applied just once each in calculation of the final result set. As an example, two of the queries I replaced with this approach utilized four UNIONs followed by two EXCEPT clauses, and each of those utilized as many as 8 JOINs in building their result sets. In one case the query dropped from 173 "explain analyze" lines to 71 "explain analyze" lines and dropped from 1.2ms execution time to 0.49ms execution time. The other query started at 136 "explain analyze" lines and dropped to 66 "explain analyze" lines. It's execution time dropped from 1.6ms to 0.66ms. This is due to the fact that each WITH clause (and the JOINS/UNIONS contained in them) are executed just once for each query and can be used multiple times later. In addition, filters can be applied to the individual result sets for each WITH clause which reduces the number of rows being worked on during later JOIN and filtering operations.
6. I specify individual columns that are returned for nearly every query utilized in the stored procedure.
7. When I have a query I need to execute whose results will be used in several other queries, I currently open the cursor for that query using the FOR ... LOOP construct to retrieve all records in the result set and build a result array using the array_append() method. I then do an unnest(my_array) AS blah inside the other queries where I need to use the results so that they do not need to be re-computed for each query. I am unsure about how efficient this method is, and I was wondering if there is some way to create a view inside a stored procedure that could be used instead. In each of the cases where I do this, the results from the set must be returned via an open cursor to my C++ application as it also requires the results from these particular queries.
Some things to note:
For most of the joins, they simply join on foreign key IDs and no additional filtering criteria are used on their information. Only a handful of the joined tables bring in additional criteria by which to filter the result set.
The approach used in 7 with cursors and building a result array which is then unnested has me worried in terms of performance. It seems to me there should be some better way to accomplish the same thing.
The stored procedure does not perform updates or inserts, only selects.
Anyway, if anyone has some insights into performance tweaks or new approaches I might try that may lead to enhanced performance, I would greatly appreciate hearing about them. I am not completely dissatisfied with the performance of the stored procedure, but this is going to be used in a very high volume environment (hundreds or possibly even thousands of calls to this stored procedure every second). The more performant it is, the less hardware I need to deploy. It currently takes about 45ms to execute the query and retrieve all of the results into the C++ application. Query execution time takes up about 16ms of that 45ms. This is on a 3-year old Core 2 Duo, so it's not exactly top-of-the-line hardware.
--
Eliot Gable
"We do not inherit the Earth from our ancestors: we borrow it from our children." ~David Brower
"I decided the words were too conservative for me. We're not borrowing from our children, we're stealing from them--and it's not even considered to be a crime." ~David Brower
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