drsnyder

<?php

class FooBar { }

$fooBar = new FooBar();

$iterations = 1e6;

$assignment = false;
$start = microtime(true);

drsnyder

{
  "items": {
    "19192": {
      "id": 19192,
      "title": "Hitman Absolution Full Disclosure Trailer",
      "ns": 6,
      "url": "/File:Hitman_Absolution_Full_Disclosure_Trailer",
      "revision": {
        "id": 37872,
        "user": "TheBlueRogue",

drsnyder

{
  "sections": [
    {
      "title": "Hitman Absolution Full Disclosure Trailer",
      "level": 1,
      "content": [],
      "images": []
    },
    {
      "title": "Description",

drsnyder

# Create a user land file for testing.
# dd if=/dev/urandom of=/tmp/urandom bs=1M count=10
#
# urandom-reads.py infile threads
# Examples:
#   time python2.6 urandom-reads.py /tmp/urandom
#   time python2.6 urandom-reads.py /dev/urandom
#
# R to generate a plot of the read time distribution at each level of concurrency
# rdt = read.csv("output.csv", header=F)

drsnyder

-- Another solution using a rollup table.
CREATE TABLE object_container_order_rollup (
  container_id INTEGER REFERENCES containers(id),
  category_id INTEGER REFERENCES categories(id),
  object_id INTEGER REFERENCES objects(id),
  type VARCHAR(32) NOT NULL,
  index INTEGER NOT NULL,
  PRIMARY KEY (container_id, type, category_id, object_id)
);

drsnyder

-- One solution to the problem. Cache the ordering in an array.
-- Pros:
  -- It's fast enough (~90ms) even with filtering
  -- Updates are atomic. You are only updating one row in one table.
   -- If the ordering is predictable (e.g. create time) then the
   -- maintenance is fast and easy because you just append to the array.

-- Cons:
  -- It requires maintenance. It's not a view and it's not a relation
    -- in the formal sense (is that right?). CREATE TYPE object_container_order_type AS (

drsnyder

-- For normal_rand() so we can create distributions that are not uniform.
-- The "real" distributions are not normal but they are closer to normal than uniform.
CREATE EXTENSION tablefunc;
BEGIN;

-- ###########################
-- The base "object" that is displayed using different either id DESC proxy
-- or scores.
CREATE TABLE objects (
  id INTEGER PRIMARY KEY,

drsnyder

for i in {1..20}; do ( time -p curl -I -s http://www.site.com )  2>&1  | grep real | cut -c6-; done | sort -n | awk '{ d[NR]=$1;  } END { print NR, "-", d[1], d[int(NR*0.5)], d[int(NR*0.95)], d[NR]; }'

drsnyder

test=# explain (analyze, buffers, verbose) update counters set count = count + 1 where count_type = 0 and count_id = 1;                                                                                     
                                                   QUERY PLAN                                                   
----------------------------------------------------------------------------------------------------------------
 Update on public.counters  (cost=0.00..5.03 rows=1 width=18) (actual time=0.036..0.036 rows=0 loops=1)
   Buffers: shared hit=6
   ->  Seq Scan on public.counters  (cost=0.00..5.03 rows=1 width=18) (actual time=0.020..0.021 rows=1 loops=1)
         Output: count_type, count_id, (count + 1), ctid
         Filter: ((counters.count_type = 0) AND (counters.count_id = 1))
         Rows Removed by Filter: 4
         Buffers: shared hit=5

drsnyder

test=# explain (analyze, buffers, verbose) update counters set count = count + 1 where count_type = 0 and count_id = 1;
                                                    QUERY PLAN                                                    ------------------------------------------------------------------------------------------------------------------
 Update on public.counters  (cost=0.00..5.74 rows=15 width=18) (actual time=0.110..0.110 rows=0 loops=1)
   Buffers: shared hit=20
   ->  Seq Scan on public.counters  (cost=0.00..5.74 rows=15 width=18) (actual time=0.014..0.054 rows=15 loops=1)
         Output: count_type, count_id, (count + 1), ctid
         Filter: ((counters.count_type = 0) AND (counters.count_id = 1))
         Rows Removed by Filter: 32
         Buffers: shared hit=5
 Total runtime: 0.137 ms