Visualizing Postgres

Transcript

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   VISUALIZING POSTGRES 2013-05-24 pgcon ottawa canada 1 2013-05-24 pgcon ottawa

   canada
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   will @leinweber 2

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   about the talk 4

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   why visualize 5

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   Anscombe's quartet 6

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   crisis 9 respond to page in the middle of the

   night whatever alert sent page isn't enough to solve the problem, or you would have automated it if you can see at a glance it's faster than grepping through logs => reduce downtime
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    anomalies 10 notice things you haven't seen before things you

    haven't planned for prompt investigation into odd behavior see the interactions between lots of things
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    capacity planning 11 should I upgrade? are there daily/weekly cycles?

    => increases robustness
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    remove guessing and gut feelings 12

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    history 13 "let's start with some history "inspiration, lessons, and

    they're just really neat
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    playfiar william 14 w 1759-1823

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    15 title, frame, labeled axes, labels in the graph, caption,

    color - in 1786 the line graph and bar chart
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    18 - in 1801 the pie chart and circle graph

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    John Snow 19

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    20 - 1854 Broad Street cholera outbreak (soho london) -

    germ theory was not yet widely accepted
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    jenny downing http://www.flickr.com/photos/jenny-pics/3761648387/ 22 There was one significant anomaly -

    none of the monks in the adjacent monastery contracted cholera. Investigation showed that this was not an anomaly, but further evidence, for they drank only beer, which they brewed themselves
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    Charles Joseph Minard 23 w 1781-187 0

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    24 Napoleon graph of 1812 (made in 1869) needs explanation,

    but has wonderful density
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    Edward Tufte 27

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    data-ink ratio data-ink ratio data-ink ratio data-ink ratio data-ink ratio

    data-ink ratio data-ink ratio data-ink ratio data-ink ratio 29
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    honesty 30 important not to mislead, even unintentionally (time zone)

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    information consists of differences that make a difference 31

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    sparklines http://tinyurl.com/sparkline 32 small multiples intense data

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    charts 33 get a little more practical

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    line 34

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    an aside 36 wIJTUPHSBN

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    horizon WJTCFSLFMFZFEVQBQFSTIPSJ[PO 37

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    http://square.github.io/cubism/ position—small color—large 39 compress vertically without loosing resolution

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    40 small multiples

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    postgres 41

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    pg_stat_statements 42 low level 8.4 Takahiro Itagaki

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    => select * from pg_stat_statements limit 1; userid | 16384

    dbid | 16385 query | SELECT "clip_versions".* FROM "clip_versions" WHERE "clip_versions"."clip_id" = ? ORDER BY created_at desc calls | 103 total_time | 37.603 rows | 632 shared_blks_hit | 504 shared_blks_read | 210 shared_blks_dirtied | 0 shared_blks_written | 0 43
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    select ((total_time::float/calls)::int / 50) * 50 as ms, lpad('', count(*)::int,

    '
    ') || ' ' || count(*) as freq from pg_stat_statements group by 1 order by 1; \watch 1 44
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    stat views pg_stat_activity pg_stat_database pg_stat_user_tables pg_stat_user_indexes pg_statio_user_tables pg_statio_user_indexes 46 transactions,

    rollbacks, bloat, cache hit
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    pg-extras https://github.com/heroku/heroku-pg-extras cache hit ratio index usage running queries blocked

    queries locks index size unused indexes sequential scans bloat 48
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    designing a system 49

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    not easy 50 there aren't concrete rules to human perception

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    data is not information 51 just having a metric in

    graphite or libretto isn't enough -- other people won't have the same context -- you probably need to do conversions such as derivatives
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    too much 52 you get X position Y position and

    a few colors aspect ratio should make lines 45º if possible
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    53 Cant line up the same time period Minimize Context

    switching
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    color http://tinyurl.com/colorrules 54 Gray or muted background soft, nature colors

    for most, bright sparingly for similar categories: single hue, vary saturation different categories: vary hue, but keep saturation
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    intents and needs NF ECB DPOUSBDUPS 55

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    generation 56 Peter Eisentraut => logging yesterday

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    log stream http://www.12factor.net/logs http://boundary.com/blog/2013/05/14/approximate-heavy- hitters-the-spacesaving-algorithm/ http://www.slideshare.net/RedRooz/harmonic-mean-for- monitored-rate-data 57

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    storage http://www.flickr.com/photos/lightmash/3183278318/ 58 storing time series data is a talk

    in and of itself =>Ronald’s talk yesterday no way i can do it justice as part of this talk rollup, table rotation
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    datascope github.com/will/datascope 59

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    overview 60 pg_stat_statements

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    overview XPSLFS
    MPPQ
    PCTFSWF
    SFTFU
    TMFFQ TUPSF
    KTPO
    QH@TUBU@TUBUFNFOUT
    PUIFST DVTUPN
    DVCJTN
    EBUB
    TPVSDF 61

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    schema CREATE TABLE stats ( id serial primary key, created_at

    timestamptz default (now()), data json); CREATE INDEX ON stats (created_at); 62
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    worker def capture_stats! s = stats DB[:stats] << {data: {

    connections: connections, stat_statements: stat_statements, cache_hit: cache_hit, locks: locks }.to_json } end 63
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    worker def stat_statements TARGET_DB[:pg_stat_statements] .select(:query, :calls, :total_time) .exclude(query: '<insufficient privilege>')

    .all end 64
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    thanks @leinweber 65