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| 1 | +<?php |
| 2 | + |
| 3 | +require_once __DIR__ . '/vendor/autoload.php'; |
| 4 | + |
| 5 | +use Pgvector\Vector; |
| 6 | + |
| 7 | +ini_set('memory_limit', '512M'); |
| 8 | + |
| 9 | +// generate random data |
| 10 | +$rows = 100000; |
| 11 | +$dimensions = 128; |
| 12 | +$embeddings = []; |
| 13 | +$categories = []; |
| 14 | +for ($i = 0; $i < $rows; $i++) { |
| 15 | + $embedding = []; |
| 16 | + for ($j = 0; $j < $dimensions; $j++) { |
| 17 | + $embedding[] = rand() / getrandmax(); |
| 18 | + } |
| 19 | + $embeddings[] = $embedding; |
| 20 | + $categories[] = rand(1, 100); |
| 21 | +} |
| 22 | + |
| 23 | +// enable extensions |
| 24 | +$db = pg_connect('postgres://localhost/pgvector_citus'); |
| 25 | +pg_query($db, 'CREATE EXTENSION IF NOT EXISTS citus'); |
| 26 | +pg_query($db, 'CREATE EXTENSION IF NOT EXISTS vector'); |
| 27 | + |
| 28 | +// GUC variables set on the session do not propagate to Citus workers |
| 29 | +// https://github.com/citusdata/citus/issues/462 |
| 30 | +// you can either: |
| 31 | +// 1. set them on the system, user, or database and reconnect |
| 32 | +// 2. set them for a transaction with SET LOCAL |
| 33 | +pg_query($db, "ALTER DATABASE pgvector_citus SET maintenance_work_mem = '512MB'"); |
| 34 | +pg_query($db, 'ALTER DATABASE pgvector_citus SET hnsw.ef_search = 20'); |
| 35 | +pg_close($db); |
| 36 | + |
| 37 | +// reconnect for updated GUC variables to take effect |
| 38 | +$db = pg_connect('postgres://localhost/pgvector_citus'); |
| 39 | + |
| 40 | +echo "Creating distributed table\n"; |
| 41 | +pg_query($db, 'DROP TABLE IF EXISTS items'); |
| 42 | +pg_query($db, 'CREATE TABLE items (id bigserial, embedding vector(128), category_id bigint, PRIMARY KEY (id, category_id))'); |
| 43 | +pg_query($db, 'SET citus.shard_count = 4'); |
| 44 | +pg_query($db, "SELECT create_distributed_table('items', 'category_id')"); |
| 45 | + |
| 46 | +echo "Loading data in parallel\n"; |
| 47 | + |
| 48 | +pg_query($db, 'COPY items (embedding, category_id) FROM STDIN'); |
| 49 | +foreach ($embeddings as $i => $e) { |
| 50 | + $row = [new Vector($e), $categories[$i]]; |
| 51 | + $line = join("\t", array_map(fn ($v) => pg_escape_string($db, $v), $row)) . "\n"; |
| 52 | + pg_put_line($db, $line); |
| 53 | +} |
| 54 | +pg_put_line($db, "\\.\n"); |
| 55 | +pg_end_copy($db); |
| 56 | + |
| 57 | +echo "Creating index in parallel\n"; |
| 58 | +pg_query($db, 'CREATE INDEX ON items USING hnsw (embedding vector_l2_ops)'); |
| 59 | + |
| 60 | +echo "Running distributed queries\n"; |
| 61 | +for ($i = 0; $i < 10; $i++) { |
| 62 | + $result = pg_query_params($db, 'SELECT id FROM items ORDER BY embedding <-> $1 LIMIT 10', [new Vector($embeddings[rand(0, $rows - 1)])]); |
| 63 | + $ids = []; |
| 64 | + while ($row = pg_fetch_array($result)) { |
| 65 | + $ids[] = $row['id']; |
| 66 | + } |
| 67 | + echo join(', ', $ids) . "\n"; |
| 68 | + pg_free_result($result); |
| 69 | +} |
| 70 | + |
| 71 | +pg_close($db); |
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