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Making Data Dance (Abstractions)

Making Data Dance (Abstractions)

Rails and the ActiveRecord gem are really handy tools to get work done, and do it quickly. They aren't a silver bullet, though. Sometimes the database is the best place to run a complicated query. Especially when you have big transactional or time-series data. Postgres has some powerful functionality that can help transform data from a giant pile of stuff into something actionable and useful. I will show how to take advantage of the JSON datatype, Common Table Expression, and materialized views to build impressive data visualizations.

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Barrett Clark

August 18, 2016
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  1. MAKING DATA DANCE Abstractions @barrettclark

  2. HARNESS HERETICAL ANTIPATTERNS FOR FUN AND PROFIT Abstractions @barrettclark

  3. BARRETT CLARK @barrettclark Abstractions @barrettclark

  4. Abstractions @barrettclark

  5. Abstractions @barrettclark Class (Model) Object Relational Mapper Database M agic

  6. DATABASE AGNOSTIC Abstractions @barrettclark

  7. ActiveRecord Object Relational Mapper Abstractions @barrettclark

  8. ActiveRecord Abstractions @barrettclark

  9. RAW SQL Abstractions @barrettclark

  10. COMPLICATED JOINS Abstractions @barrettclark

  11. Category.joins(articles: [{ comments: :guest }, :tags]) http://guides.rubyonrails.org/active_record_querying.html#using-array-hash-of-named-associations Abstractions @barrettclark ???

  12. SELECT categories.* FROM categories INNER JOIN articles ON articles.category_id =

    categories.id INNER JOIN comments ON comments.article_id = articles.id INNER JOIN guests ON guests.comment_id = comments.id INNER JOIN tags ON tags.article_id = articles.id http://guides.rubyonrails.org/active_record_querying.html#using-array-hash-of-named-associations Abstractions @barrettclark Category.joins(articles: [{ comments: :guest }, :tags])
  13. DEEPER DATABASE FUNCTIONALITY Abstractions @barrettclark

  14. BUT DATABASE PORTABILITY?! Abstractions @barrettclark

  15. https://flic.kr/p/eg4hih Abstractions @barrettclark

  16. It just doesn't work like that. Database portability pipe dream

    Abstractions @barrettclark
  17. Different databases are different. Abstractions @barrettclark

  18. You chose your database for a reason. Use it! Abstractions

    @barrettclark
  19. CAVEATS • Long-running queries • Connection pool Abstractions @barrettclark

  20. LET'S GET OUR HANDS DIRTY Abstractions @barrettclark

  21. Abstractions @barrettclark

  22. WINDOW FUNCTIONS Abstractions @barrettclark

  23. –Postgres Documentation A window function performs a calculation across a

    set of table rows that are somehow related to the current row. Abstractions @barrettclark
  24. –Barrett Clark Fold data from other rows into this row

    Abstractions @barrettclark
  25. WINDOW FUNCTION GREATEST HITS • lead() • lag() • first_value()

    • last_value() • row_number() Abstractions @barrettclark
  26. id fruit 1 apple 2 apple 3 apple 4 pear

    5 apple 6 pear 7 pear 8 pear 9 pear 10 banana Abstractions @barrettclark
  27. SELECT *,LEAD(id) OVER(), LAG(id) OVER() FROM fruits; id | fruit

    | lead | lag ----+--------+------+----- 1 | apple | 2 | 2 | apple | 3 | 1 3 | apple | 4 | 2 4 | pear | 5 | 3 5 | apple | 6 | 4 6 | pear | 7 | 5 7 | pear | 8 | 6 8 | pear | 9 | 7 9 | pear | 10 | 8 10 | banana | | 9 (10 rows) http://sqlfiddle.com/#!15/230c3b/2 Abstractions @barrettclark
  28. –Postgres Documentation A window function performs a calculation across a

    set of table rows that are somehow related to the current row. Abstractions @barrettclark
  29. Abstractions @barrettclark https://flic.kr/p/7KGqEY

  30. SELECT id, fruit, FIRST_VALUE(id) OVER(PARTITION BY fruit ORDER BY id)

    FROM fruits; id | fruit | first_value ----+--------+------------- 1 | apple | 1 2 | apple | 1 3 | apple | 1 5 | apple | 1 10 | banana | 10 4 | pear | 4 6 | pear | 4 7 | pear | 4 8 | pear | 4 9 | pear | 4 (10 rows) http://sqlfiddle.com/#!15/230c3b Abstractions @barrettclark
  31. SELECT *, FIRST_VALUE(id) OVER(PARTITION BY fruit ORDER BY id), ROW_NUMBER()

    OVER(PARTITION BY fruit ORDER BY id) FROM fruits; id | fruit | first_value | row_number ----+--------+-------------+------------ 1 | apple | 1 | 1 2 | apple | 1 | 2 3 | apple | 1 | 3 5 | apple | 1 | 4 10 | banana | 10 | 1 4 | pear | 4 | 1 6 | pear | 4 | 2 7 | pear | 4 | 3 8 | pear | 4 | 4 9 | pear | 4 | 5 (10 rows) http://sqlfiddle.com/#!15/230c3b Abstractions @barrettclark
  32. PRACTICAL EXAMPLE Chat App Abstractions @barrettclark

  33. SELECT id, message, room_id, user_id FROM messages ORDER BY id;

    id | message | room_id | user_id ----+-----------------------------+---------+--------- 1 | Leaving for the airport now | 1 | 1337 2 | Flight just landed! | 1 | 1337 3 | waiting on an uber | 2 | 1337 4 | omw y'all! | 1 | 1337 9 | hello, world | 1 | 27 (5 rows) Abstractions @barrettclark
  34. SELECT id, message, room_id, user_id, LAG(user_id) OVER( PARTITION BY room_id

    ORDER BY room_id, id ) AS prev_user_id FROM messages ORDER BY 3, 1; Look back Defines the groups of rows to evaluate against the current row Abstractions @barrettclark
  35. id | message | room_id | user_id | prev_user_id ----+-----------------------------+---------+---------+--------------

    1 | Leaving for the airport now | 1 | 1337 | 2 | Flight just landed! | 1 | 1337 | 1337 4 | omw y'all! | 1 | 1337 | 1337 9 | hello, world | 1 | 27 | 1337 3 | waiting on an uber | 2 | 1337 | (5 rows) SELECT id, message, room_id, user_id, LAG(user_id) OVER( PARTITION BY room_id ORDER BY room_id, id ) AS prev_user_id FROM messages ORDER BY 3, 1; Abstractions @barrettclark
  36. SELECT id, message, room_id, user_id, LAG(user_id) OVER( PARTITION BY room_id

    ORDER BY room_id, id ) AS prev_user_id FROM messages ORDER BY 3, 1; ProTip™ 3 1 2 4 5 Abstractions @barrettclark
  37. class Message < ActiveRecord::Base def self.window_example sql = <<-SQL SELECT

    id, message, room_id, user_id, LAG(user_id) OVER(PARTITION BY room_id ORDER BY room_id, id) AS prev_user_id FROM messages ORDER BY 3, 1; SQL connection.execute(sql) end end Abstractions @barrettclark
  38. TOO ANTI-PATTERN FOR YOU? Abstractions @barrettclark

  39. module PGConnection def conn config = YAML.load_file(File.open('config/database.yml'))['development'] @conn ||= PG.connect(

    :dbname => config['database'], :user => config['username'], :password => config['password'], :host => config['host'] || 'localhost' ) end end class Antipattern extend PGConnection def self.window_example sql = <<-SQL SELECT id, message, room_id, user_id, LAG(user_id) OVER(PARTITION BY room_id ORDER BY room_id, id) AS prev_user_id FROM messages ORDER BY 3, 1; SQL conn.exec(sql).values end end Abstractions @barrettclark
  40. MODELS DO NOT HAVE TO BE BACKED BY ACTIVERECORD Or

    even persisted in the database. Abstractions @barrettclark
  41. QUESTIONS WE CAN NOW ANSWER • When did something change?

    • When did someone leave a place? • How long did each thing last? • How long did people stay in which places? • Enter / Exit / Change events Abstractions @barrettclark
  42. Abstractions @barrettclark https://flic.kr/p/5b8cq3

  43. SUBQUERIES Abstractions @barrettclark

  44. SUBQUERY • To filter and group • For a field

    value • In a join Abstractions @barrettclark
  45. BASE QUERY Abstractions @barrettclark

  46. SELECT id, phone, major, minor, reading_timestamp, LEAD(minor) OVER ( PARTITION

    BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY 2, 5; “For a given phone, pull in the next minor field” Abstractions @barrettclark
  47. WHEN DID SOMETHING CHANGE? Abstractions @barrettclark

  48. SELECT major, minor, next_minor, COUNT(*) FROM ( SELECT id, phone,

    major, minor, reading_timestamp, LEAD(minor) OVER ( PARTITION BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY 2, 5 ) AS beacon_readings_lead WHERE major = 1 AND minor != next_minor GROUP BY major, minor, next_minor ORDER BY major, minor, next_minor; Abstractions @barrettclark
  49. YO DAWG, I HEARD YOU LIKE QUERIES Abstractions @barrettclark

  50. SELECT major, minor, next_minor, COUNT(*) FROM ( SELECT id, phone,

    major, minor, reading_timestamp, LEAD(minor) OVER ( PARTITION BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY 2, 5 ) AS beacon_readings_lead WHERE major = 1 AND minor != next_minor GROUP BY major, minor, next_minor ORDER BY major, minor, next_minor; Abstractions @barrettclark
  51. major | minor | next_minor | count -------+-------+------------+------- 1 |

    0 | 1 | 18 1 | 0 | 2 | 3 1 | 0 | 3 | 23 1 | 0 | 4 | 7 1 | 1 | 0 | 19 1 | 1 | 2 | 59 1 | 1 | 3 | 158 1 | 1 | 4 | 44 1 | 2 | 0 | 5 1 | 2 | 1 | 59 1 | 2 | 3 | 85 1 | 2 | 4 | 40 1 | 3 | 0 | 21 1 | 3 | 1 | 154 1 | 3 | 2 | 85 1 | 3 | 4 | 52 1 | 4 | 0 | 6 1 | 4 | 1 | 49 1 | 4 | 2 | 42 1 | 4 | 3 | 45 (20 rows) Abstractions @barrettclark
  52. Abstractions @barrettclark

  53. https://flic.kr/p/9tT9Yh Abstractions @barrettclark

  54. REFACTOR Abstractions @barrettclark

  55. CTE Common Table Expression Abstractions @barrettclark

  56. SELECT major, minor, next_minor, COUNT(*) FROM ( SELECT id, phone,

    major, minor, reading_timestamp, LEAD(minor) OVER ( PARTITION BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY 2, 5 ) AS beacon_readings_lead WHERE major = 1 AND minor != next_minor GROUP BY major, minor, next_minor ORDER BY major, minor, next_minor; Abstractions @barrettclark
  57. WITH beacon_readings_lead AS ( SELECT id, phone, major, minor, reading_timestamp,

    LEAD(minor) OVER ( PARTITION BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY 2, 5 ) SELECT major, minor, next_minor, COUNT(*) FROM beacon_readings_lead WHERE major = 1 AND minor != next_minor GROUP BY major, minor, next_minor ORDER BY major, minor, next_minor; Abstractions @barrettclark
  58. WITH interval_query AS ( SELECT (ts ||' hour')::INTERVAL AS hour_interval

    FROM generate_series(0,23) AS ts ), time_series AS ( SELECT DATE_TRUNC('hour', NOW()) + INTERVAL '60 min' * ROUND(DATE_PART('minute', NOW()) / 60.0) - interval_query.hour_interval AS start_time FROM interval_query ), time_intervals AS ( SELECT start_time, start_time + '1 hour'::INTERVAL AS end_time FROM time_series ORDER BY start_time ), reading_counts AS ( SELECT f.start_time, f.end_time, br.minor, COUNT(DISTINCT br.phone) readings FROM beacon_readings br RIGHT JOIN time_intervals f ON br.reading_timestamp >= f.start_time AND br.reading_timestamp < f.end_time AND br.major = 1 GROUP BY f.start_time, f.end_time, br.minor ORDER BY f.start_time, br.minor ) SELECT * FROM reading_counts; Abstractions @barrettclark
  59. Abstractions @barrettclark

  60. Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition

    Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Repetition Abstractions @barrettclark
  61. VIEW Stored Query Abstractions @barrettclark

  62. CREATE OR REPLACE VIEW beacon_readings_lead_view AS SELECT id, phone, major,

    minor, reading_timestamp, LEAD(minor) OVER ( PARTITION BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY 2, 5 ; Abstractions @barrettclark
  63. class CreateLeadView < ActiveRecord::Migration def up execute <<-SQL.strip_heredoc CREATE OR

    REPLACE VIEW beacon_readings_lead_view AS SELECT ID, phone, major, minor, reading_timestamp, LEAD(minor) OVER ( PARTITION BY phone ORDER BY phone, reading_timestamp ) AS next_minor FROM beacon_readings ORDER BY phone, reading_timestamp; SQL end def down sql = "DROP VIEW IF EXISTS beacon_readings_lead_view;" execute(sql) end end Abstractions @barrettclark
  64. SELECT major, minor, next_minor, COUNT(*) FROM beacon_readings_lead_view WHERE major =

    1 AND minor != next_minor GROUP BY major, minor, next_minor ORDER BY major, minor, next_minor; Abstractions @barrettclark
  65. BUSINESS LOGIC IN THE DATABASE?!? Abstractions @barrettclark

  66. YOU Get to decide where your code runs Abstractions @barrettclark

  67. https://flic.kr/p/2MW7SY Abstractions @barrettclark

  68. MY QUERY IS TOO SLOW Abstractions @barrettclark

  69. DO THE HEAVY LIFTING IN A SEPARATE PROCESS Abstractions @barrettclark

  70. MATERIALIZED VIEW Stored query AND data Abstractions @barrettclark

  71. CREATE MATERIALIZED VIEW beacon_readings_lead_lag_mv AS SELECT * FROM beacon_readings_lead_lag_view WHERE

    reading_timestamp >= NOW() - '1 day'::INTERVAL; CREATE INDEX index_beacon_readings_mv_on_major ON beacon_readings_lead_lag_mv USING btree( major ASC NULLS LAST ); CREATE INDEX index_beacon_readings_mv_on_phone ON beacon_readings_lead_lag_mv USING btree( phone COLLATE "default" ASC NULLS LAST ); CREATE INDEX index_beacon_readings_mv_on_reading_timestamp ON beacon_readings_lead_lag_mv USING btree( reading_timestamp ASC NULLS LAST ); Abstractions @barrettclark
  72. DATA Abstractions @barrettclark https://flic.kr/p/khS6jn

  73. REFRESH MATERIALIZED VIEW CONCURRENTLY beacon_readings_lead_lag_mv; Available starting in 9.4 Abstractions

    @barrettclark
  74. namespace :db do namespace :heroku do # https://devcenter.heroku.com/articles/scheduler desc 'Update

    the materialized view(s)' task :update_materialized_view => :environment do sql = 'REFRESH MATERIALIZED VIEW beacon_readings_lead_lag_mv;' ActiveRecord::Base.connection.execute(sql) end end end Abstractions @barrettclark
  75. Abstractions @barrettclark https://flic.kr/p/bVUL7

  76. SUBQUERY FOR A FIELD VALUE Abstractions @barrettclark

  77. SELECT id, phone, ( SELECT MIN(id) FROM beacon_readings_lead_lag_mv WHERE major

    = br1.major AND minor = 0 AND phone = br1.phone AND id >= br1.id ) AS session_close_id, minor, next_beacon_minor, reading_timestamp FROM beacon_readings_lead_lag_mv br1 WHERE major = 2 AND minor != next_beacon_minor ORDER BY phone, reading_timestamp; Abstractions @barrettclark
  78. SELECT id, phone, ( SELECT MIN(id) FROM beacon_readings_lead_lag_mv WHERE major

    = br1.major AND minor = 0 AND phone = br1.phone AND id >= br1.id ) AS session_close_id, minor, next_beacon_minor, reading_timestamp FROM beacon_readings_lead_lag_mv br1 WHERE major = 2 AND minor != next_beacon_minor ORDER BY phone, reading_timestamp; Abstractions @barrettclark
  79. Abstractions @barrettclark

  80. OTHER USEFUL THINGS Abstractions @barrettclark

  81. POSTGRES • Install from source • Install via package manager

    • Heroku's Postgres.app • Postgres 9.5.4 • PostGIS 2.2.2 Abstractions @barrettclark
  82. POSTGRES • Database GUI tools • pgAdmin3 (free) • Navicat

    (free trials) Abstractions @barrettclark
  83. POSTGRES • Visual query plan • http://explain.depesz.com/ • http://tatiyants.com/pev Abstractions

    @barrettclark
  84. Abstractions @barrettclark http://explain.depesz.com

  85. Abstractions @barrettclark http://tatiyants.com/pev

  86. CAUTION!!! Different environments are different Abstractions @barrettclark

  87. DATATYPES • Array • DateRange and TSRange • JSON, JSONB

    (9.4) • UUID http://edgeguides.rubyonrails.org/active_record_postgresql.html Abstractions @barrettclark
  88. UPSERT!!! New in Postgres 9.5

  89. PARALLEL SEQUENTIAL SCAN, JOINS, AND AGGREGATES New in Postgres 9.6

  90. FUTURE YOU WILL THANK YOU Abstractions @barrettclark

  91. RECAP Abstractions @barrettclark

  92. IT'S OK TO WRITE SQL Abstractions @barrettclark

  93. REFACTOR • Common Table Expression (CTE) • View • Materialized

    View Abstractions @barrettclark
  94. I'M NOT SAYING DO EVERYTHING IN THE DATABASE Abstractions @barrettclark

  95. POSTGRESQL IS AWESOME Abstractions @barrettclark

  96. Abstractions @barrettclark

  97. THANK YOU! Abstractions @barrettclark