mirror of https://github.com/postgres/postgres
201 lines
8.4 KiB
Plaintext
201 lines
8.4 KiB
Plaintext
An attempt at some sort of Full Text Indexing for PostgreSQL.
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The included software is an attempt to add some sort of Full Text Indexing
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support to PostgreSQL. I mean by this that we can ask questions like:
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Give me all rows that have 'still' and 'nash' in the 'artist' or 'title'
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fields.
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Ofcourse we can write this as:
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select * from cds where (artist ~* 'stills' or title ~* 'stills') and
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(artist ~* 'nash' or title ~* 'nash');
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But this does not use any indices, and therefore, if your database
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gets very large, it will not have very high performance (the above query
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requires a sequential scan of the table).
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The approach used by this add-on is to define a trigger on the table and
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columns you want to do these queries on. On every insert to the table, it
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takes the value in the specified columns, breaks the text in these columns
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up into pieces, and stores all sub-strings into another table, together
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with a reference to the row in the original table that contained this
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sub-string (it uses the oid of that row).
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By now creating an index over the 'fti-table', we can search for
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substrings that occur in the original table. By making a join between
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the fti-table and the orig-table, we can get the actual rows we want
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(this can also be done by using subselects - but subselects are currently
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inefficient in PostgreSQL, and maybe there're other ways too).
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The trigger code also allows an array called StopWords, that prevents
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certain words from being indexed.
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As an example we take the previous query, where we assume we have all
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sub-strings in the table 'cds-fti':
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select c.*
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from cds c, cds-fti f1, cds-fti f2
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where f1.string ~ '^stills' and
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f2.string ~ '^nash' and
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f1.id = c.oid and
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f2.id = c.oid ;
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We can use the ~ (case-sensitive regular expression) here, because of
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the way sub-strings are built: from right to left, ie. house -> 'se' +
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'use' + 'ouse' + 'house'. If a ~ search starts with a ^ (match start of
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string), btree indices can be used by PostgreSQL.
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Now, how do we create the trigger that maintains the fti-table? First: the
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fti-table should have the following schema:
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create cds-fti ( string varchar(N), id oid ) without oids;
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Don't change the *names* of the columns, the varchar() can in fact also
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be of text-type. If you do use varchar, make sure the largest possible
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sub-string will fit.
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The create the function that contains the trigger::
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create function fti() returns trigger as
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'/path/to/fti.so' language 'C';
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And finally define the trigger on the 'cds' table:
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create trigger cds-fti-trigger after update or insert or delete on cds
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for each row execute procedure fti(cds-fti, artist, title);
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Here, the trigger will be defined on table 'cds', it will create
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sub-strings from the fields 'artist' and 'title', and it will place
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those sub-strings in the table 'cds-fti'.
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Now populate the table 'cds'. This will also populate the table 'cds-fti'.
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It's fastest to populate the table *before* you create the indices. Use the
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supplied 'fti.pl' to assist you with this.
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Before you start using the system, you should at least have the following
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indices:
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create index cds-fti-idx on cds-fti (string); -- String matching
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create index cds-fti-idx on cds-fti (id); -- For deleting a cds row
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create index cds-oid-idx on cds (oid); -- For joining cds to cds-fti
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To get the most performance out of this, you should have 'cds-fti'
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clustered on disk, ie. all rows with the same sub-strings should be
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close to each other. There are 3 ways of doing this:
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1. After you have created the indices, execute 'cluster cds-fti-idx on cds-fti'.
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2. Do a 'select * into tmp-table from cds-fti order by string' *before*
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you create the indices, then 'drop table cds-fti' and
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'alter table tmp-table rename to cds-fti'
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3. *Before* creating indices, dump the contents of the cds-fti table using
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'pg_dump -a -t cds-fti dbase-name', remove the \connect
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from the beginning and the \. from the end, and sort it using the
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UNIX 'sort' program, and reload the data.
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Method 1 is very slow, 2 a lot faster, and for very large tables, 3 is
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preferred.
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BENCH:
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~~~~~
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Maarten Boekhold <maartenb@dutepp0.et.tudelft.nl>
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The following data was generated by the 'timings.sh' script included
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in this directory. It uses a very large table with music-related
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articles as a source for the fti-table. The tables used are:
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product : contains product information : 540.429 rows
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artist_fti : fti table for product : 4.501.321 rows
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clustered : same as above, only clustered : 4.501.321 rows
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A sequential scan of the artist_fti table (and thus also the clustered table)
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takes around 6:16 minutes....
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Unfortunately I cannot provide anybody else with this test-data, since I
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am not allowed to redistribute the data (it's a database being sold by
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a couple of wholesale companies). Anyways, it's megabytes, so you probably
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wouldn't want it in this distribution anyways.
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I haven't tested this with less data.
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The test-machine is a Pentium 133, 64 MB, Linux 2.0.32 with the database
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on a 'QUANTUM BIGFOOT_CY4320A, 4134MB w/67kB Cache, CHS=8960/15/63'. This
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is a very slow disk.
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The postmaster was running with:
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postmaster -i -b /usr/local/pgsql/bin/postgres -S 1024 -B 256 \
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-o -o /usr/local/pgsql/debug-output -F -d 1
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('trashing' means a 'select count(*) from artist_fti' to completely trash
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any disk-caches and buffers....)
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TESTING ON UNCLUSTERED FTI
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trashing
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1: ^lapton and ^ric : 0.050u 0.000s 5m37.484s 0.01%
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2: ^lapton and ^ric : 0.050u 0.030s 5m32.447s 0.02%
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3: ^lapton and ^ric : 0.030u 0.020s 5m28.822s 0.01%
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trashing
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1: ^lling and ^tones : 0.020u 0.030s 0m54.313s 0.09%
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2: ^lling and ^tones : 0.040u 0.030s 0m5.057s 1.38%
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3: ^lling and ^tones : 0.010u 0.050s 0m2.072s 2.89%
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trashing
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1: ^aughan and ^evie : 0.020u 0.030s 0m26.241s 0.19%
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2: ^aughan and ^evie : 0.050u 0.010s 0m1.316s 4.55%
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3: ^aughan and ^evie : 0.030u 0.020s 0m1.029s 4.85%
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trashing
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1: ^lling : 0.040u 0.010s 0m55.104s 0.09%
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2: ^lling : 0.030u 0.030s 0m4.716s 1.27%
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3: ^lling : 0.040u 0.010s 0m2.157s 2.31%
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trashing
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1: ^stev and ^ray and ^vaugh : 0.040u 0.000s 1m5.630s 0.06%
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2: ^stev and ^ray and ^vaugh : 0.050u 0.020s 1m3.561s 0.11%
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3: ^stev and ^ray and ^vaugh : 0.050u 0.010s 1m5.923s 0.09%
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trashing
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1: ^lling (no join) : 0.050u 0.020s 0m24.139s 0.28%
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2: ^lling (no join) : 0.040u 0.040s 0m1.087s 7.35%
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3: ^lling (no join) : 0.020u 0.030s 0m0.772s 6.48%
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trashing
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1: ^vaughan (no join) : 0.040u 0.030s 0m9.075s 0.77%
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2: ^vaughan (no join) : 0.030u 0.010s 0m0.609s 6.56%
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3: ^vaughan (no join) : 0.040u 0.010s 0m0.503s 9.94%
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trashing
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1: ^rol (no join) : 0.020u 0.030s 0m49.898s 0.10%
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2: ^rol (no join) : 0.030u 0.020s 0m3.136s 1.59%
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3: ^rol (no join) : 0.030u 0.020s 0m1.231s 4.06%
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TESTING ON CLUSTERED FTI
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trashing
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1: ^lapton and ^ric : 0.020u 0.020s 2m17.120s 0.02%
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2: ^lapton and ^ric : 0.030u 0.020s 2m11.767s 0.03%
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3: ^lapton and ^ric : 0.040u 0.010s 2m8.128s 0.03%
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trashing
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1: ^lling and ^tones : 0.020u 0.030s 0m18.179s 0.27%
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2: ^lling and ^tones : 0.030u 0.010s 0m1.897s 2.10%
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3: ^lling and ^tones : 0.040u 0.010s 0m1.619s 3.08%
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trashing
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1: ^aughan and ^evie : 0.070u 0.010s 0m11.765s 0.67%
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2: ^aughan and ^evie : 0.040u 0.010s 0m1.198s 4.17%
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3: ^aughan and ^evie : 0.030u 0.020s 0m0.872s 5.73%
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trashing
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1: ^lling : 0.040u 0.000s 0m28.623s 0.13%
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2: ^lling : 0.030u 0.010s 0m2.339s 1.70%
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3: ^lling : 0.030u 0.010s 0m1.975s 2.02%
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trashing
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1: ^stev and ^ray and ^vaugh : 0.020u 0.010s 0m17.667s 0.16%
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2: ^stev and ^ray and ^vaugh : 0.030u 0.010s 0m3.745s 1.06%
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3: ^stev and ^ray and ^vaugh : 0.030u 0.020s 0m3.439s 1.45%
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trashing
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1: ^lling (no join) : 0.020u 0.040s 0m2.218s 2.70%
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2: ^lling (no join) : 0.020u 0.020s 0m0.506s 7.90%
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3: ^lling (no join) : 0.030u 0.030s 0m0.510s 11.76%
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trashing
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1: ^vaughan (no join) : 0.040u 0.050s 0m2.048s 4.39%
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2: ^vaughan (no join) : 0.030u 0.020s 0m0.332s 15.04%
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3: ^vaughan (no join) : 0.040u 0.010s 0m0.318s 15.72%
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trashing
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1: ^rol (no join) : 0.020u 0.030s 0m2.384s 2.09%
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2: ^rol (no join) : 0.020u 0.030s 0m0.676s 7.39%
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3: ^rol (no join) : 0.020u 0.030s 0m0.697s 7.17%
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