On Thu, 16 Jan 2020 12:59:11 +0900 nuko yokohama <nuko.yokoh...@gmail.com> wrote:
> Aggregate operation of user-defined type cannot be specified > (commit e150d964df7e3aeb768e4bae35d15764f8abd284) > > A SELECT statement using the MIN() and MAX() functions can be executed on a > user-defined type column that implements the aggregate functions MIN () and > MAX (). > However, if the same SELECT statement is specified in the AS clause of > CREATE INCREMENTAL MATERIALIZED VIEW, the following error will occur. > > ``` > SELECT MIN(data) data_min, MAX(data) data_max FROM foo; > data_min | data_max > ----------+---------- > 1/3 | 2/3 > (1 row) > > CREATE INCREMENTAL MATERIALIZED VIEW foo_min_imv AS SELECT MIN(data) > data_min FROM foo; > psql:extension-agg.sql:14: ERROR: aggregate function min is not supported > CREATE INCREMENTAL MATERIALIZED VIEW foo_max_imv AS SELECT MAX(data) > data_max FROM foo; > psql:extension-agg.sql:15: ERROR: aggregate function max is not supported > ``` > > Does query including user-defined type aggregate operation not supported by > INCREMENTAL MATERIALIZED VIEW? The current implementation supports only built-in aggregate functions, so user-defined aggregates are not supported, although it is allowed before. This is because we can not know how user-defined aggregates behave and if it can work safely with IVM. Min/Max on your fraction type may work well, but it is possible that some user-defined aggregate functions named min or max behave in totally different way than we expected. In future, maybe it is possible support user-defined aggregates are supported by extending pg_aggregate and adding support functions for IVM, but there is not still a concrete plan for now. BTW, the following error message doesn't look good because built-in min is supported, so I will improve it. ERROR: aggregate function min is not supported Regards, Yugo Nagata > > An execution example is shown below. > > ``` > [ec2-user@ip-10-0-1-10 ivm]$ cat extension-agg.sql > -- > -- pg_fraction: https://github.com/nuko-yokohama/pg_fraction > -- > DROP EXTENSION IF EXISTS pg_fraction CASCADE; > DROP TABLE IF EXISTS foo CASCADE; > > CREATE EXTENSION IF NOT EXISTS pg_fraction; > \dx > \dT+ fraction > > CREATE TABLE foo (id int, data fraction); > INSERT INTO foo (id, data) VALUES (1,'2/3'),(2,'1/3'),(3,'1/2'); > SELECT MIN(data) data_min, MAX(data) data_max FROM foo; > CREATE INCREMENTAL MATERIALIZED VIEW foo_min_imv AS SELECT MIN(data) > data_min FROM foo; > CREATE INCREMENTAL MATERIALIZED VIEW foo_max_imv AS SELECT MAX(data) > data_max FROM foo; > > SELECT MIN(id) id_min, MAX(id) id_max FROM foo; > CREATE INCREMENTAL MATERIALIZED VIEW foo_id_imv AS SELECT MIN(id) id_min, > MAX(id) id_max FROM foo; > ``` > > Best regards. > > 2018年12月27日(木) 21:57 Yugo Nagata <nag...@sraoss.co.jp>: > > > Hi, > > > > I would like to implement Incremental View Maintenance (IVM) on > > PostgreSQL. > > IVM is a technique to maintain materialized views which computes and > > applies > > only the incremental changes to the materialized views rather than > > recomputate the contents as the current REFRESH command does. > > > > I had a presentation on our PoC implementation of IVM at PGConf.eu 2018 > > [1]. > > Our implementation uses row OIDs to compute deltas for materialized > > views. > > The basic idea is that if we have information about which rows in base > > tables > > are contributing to generate a certain row in a matview then we can > > identify > > the affected rows when a base table is updated. This is based on an idea of > > Dr. Masunaga [2] who is a member of our group and inspired from ID-based > > approach[3]. > > > > In our implementation, the mapping of the row OIDs of the materialized view > > and the base tables are stored in "OID map". When a base relation is > > modified, > > AFTER trigger is executed and the delta is recorded in delta tables using > > the transition table feature. The accual udpate of the matview is triggerd > > by REFRESH command with INCREMENTALLY option. > > > > However, we realize problems of our implementation. First, WITH OIDS will > > be removed since PG12, so OIDs are no longer available. Besides this, it > > would > > be hard to implement this since it needs many changes of executor nodes to > > collect base tables's OIDs during execuing a query. Also, the cost of > > maintaining > > OID map would be high. > > > > For these reasons, we started to think to implement IVM without relying on > > OIDs > > and made a bit more surveys. > > > > We also looked at Kevin Grittner's discussion [4] on incremental matview > > maintenance. In this discussion, Kevin proposed to use counting algorithm > > [5] > > to handle projection views (using DISTNICT) properly. This algorithm need > > an > > additional system column, count_t, in materialized views and delta tables > > of > > base tables. > > > > However, the discussion about IVM is now stoped, so we would like to > > restart and > > progress this. > > > > > > Through our PoC inplementation and surveys, I think we need to think at > > least > > the followings for implementing IVM. > > > > 1. How to extract changes on base tables > > > > I think there would be at least two approaches for it. > > > > - Using transition table in AFTER triggers > > - Extracting changes from WAL using logical decoding > > > > In our PoC implementation, we used AFTER trigger and transition tables, > > but using > > logical decoding might be better from the point of performance of base > > table > > modification. > > > > If we can represent a change of UPDATE on a base table as query-like > > rather than > > OLD and NEW, it may be possible to update the materialized view directly > > instead > > of performing delete & insert. > > > > > > 2. How to compute the delta to be applied to materialized views > > > > Essentially, IVM is based on relational algebra. Theorically, changes on > > base > > tables are represented as deltas on this, like "R <- R + dR", and the > > delta on > > the materialized view is computed using base table deltas based on "change > > propagation equations". For implementation, we have to derive the > > equation from > > the view definition query (Query tree, or Plan tree?) and describe this as > > SQL > > query to compulte delta to be applied to the materialized view. > > > > There could be several operations for view definition: selection, > > projection, > > join, aggregation, union, difference, intersection, etc. If we can > > prepare a > > module for each operation, it makes IVM extensable, so we can start a > > simple > > view definition, and then support more complex views. > > > > > > 3. How to identify rows to be modifed in materialized views > > > > When applying the delta to the materialized view, we have to identify > > which row > > in the matview is corresponding to a row in the delta. A naive method is > > matching > > by using all columns in a tuple, but clearly this is unefficient. If > > thematerialized > > view has unique index, we can use this. Maybe, we have to force > > materialized views > > to have all primary key colums in their base tables. In our PoC > > implementation, we > > used OID to identify rows, but this will be no longer available as said > > above. > > > > > > 4. When to maintain materialized views > > > > There are two candidates of the timing of maintenance, immediate (eager) > > or deferred. > > > > In eager maintenance, the materialized view is updated in the same > > transaction > > where the base table is updated. In deferred maintenance, this is done > > after the > > transaction is commited, for example, when view is accessed, as a response > > to user > > request, etc. > > > > In the previous discussion[4], it is planned to start from "eager" > > approach. In our PoC > > implementaion, we used the other aproach, that is, using REFRESH command > > to perform IVM. > > I am not sure which is better as a start point, but I begin to think that > > the eager > > approach may be more simple since we don't have to maintain base table > > changes in other > > past transactions. > > > > In the eager maintenance approache, we have to consider a race condition > > where two > > different transactions change base tables simultaneously as discussed in > > [4]. > > > > > > [1] > > https://www.postgresql.eu/events/pgconfeu2018/schedule/session/2195-implementing-incremental-view-maintenance-on-postgresql/ > > [2] > > https://ipsj.ixsq.nii.ac.jp/ej/index.php?active_action=repository_view_main_item_detail&page_id=13&block_id=8&item_id=191254&item_no=1 > > (Japanese only) > > [3] https://dl.acm.org/citation.cfm?id=2750546 > > [4] > > https://www.postgresql.org/message-id/flat/1368561126.64093.YahooMailNeo%40web162904.mail.bf1.yahoo.com > > [5] https://dl.acm.org/citation.cfm?id=170066 > > > > Regards, > > -- > > Yugo Nagata <nag...@sraoss.co.jp> > > > > -- Yugo NAGATA <nag...@sraoss.co.jp>
