How to implement

yarn add --dev husky

yarn add --dev lint-staged

"scripts": {
    "precommit": "lint-staged"
  },
  "lint-staged": {
   "{app,spec,lib}/**/*.rb": [
      "bundle exec rubocop -a",
      "git add"
    ]
  }

_{Auto Formatting Javascript}

yarn add --dev prettier

   "app/**/*.{js,es6,jsx,scss,css}": [
      "./node_modules/prettier/bin-prettier.js --trailing-comma es5 --write",
      "git add"
    ]

{
  "name": "starter",
  "private": true,
  "dependencies": {
    "@rails/webpacker": "^3.3.0"
  },
  "scripts": {
    "precommit": "lint-staged"
  },
  "lint-staged": {
    "app/**/*.{js,es6,jsx,scss,css}": [
      "./node_modules/prettier/bin-prettier.js --trailing-comma es5 --write",
      "git add"
    ],
    "{app,test}/**/*.rb": [
      "bundle exec rubocop -a",
      "git add"
    ]
  },
  "devDependencies": {
    "husky": "^0.13.4",
    "lint-staged": "^3.6.0",
    "prettier": "^1.4.2",
    "webpack-dev-server": "^2.11.1"
  }
}

x = {1, 2, 3}
# to get the value use
x[0]

x[0] = 10

undefined method '[]=' for Tuple(Int32, Int32)

(1..100).minmax

Note: Since we just mentioned minmax, have a look at minmax_by method as well. It would let you apply a block of code over your range and then return the minimum and maximum based on the returned collection.

["1234", "12", "123"].minmax_by { |i| i.size }
# => {"12", "1234"}

Tuple(Int32, Int32).from([1, 2])

argument to splat must be a tuple, not Array(Int32)

Named Tuple

data = {x: 1, y: 2}
# to get the value
data[:x]
# raises errors when we try to change it
data[:x] = 1

def print_date(year = nil, month = nil, day = nil)
  puts "#{year}/#{month}/#{day}"
end
birth_day = { year: 1990, month: 4, day: 3}
print_date(**birth_day)
card_expiry = { year: 2020, month: 1}
print_date(**card_expiry)

NamedTuple(name: String, val: String).from({"name" => "number", "val" => "Harisankar P S"}

k = 42.as(Int32 | String)
NamedTuple(name: String, val: String).from({"name" => "number", "val" => K}

cast from Int32 to String failed, at /usr/local/Cellar/crystal-lang/0.23.1_1/src/class.cr:41:5:41 (TypeCastError)
0x10e8f1085: *CallStack::unwind:Array(Pointer(Void)) at ??
0x10e8f1021: *CallStack#initialize:Array(Pointer(Void)) at ??
0x10e8f0ff8: *CallStack::new:CallStack at ??
0x10e8ec295: *raise<TypeCastError>:NoReturn at ??
0x10e90feb8: *String@Object::cast<(Int32 | String)>:String at ??
0x10e95faa3: *NamedTuple(name: String:Class, val: String:Class)@NamedTuple(T)#from<Hash(String, Int32 | String)>:NamedTuple(name: String, val: String) at ??
0x10e95f787: *NamedTuple(name: String, val: String)@NamedTuple(T)::from<Hash(String, Int32 | String)>:NamedTuple(name: String, val: String) at ??
0x10e8ef8a6: *__icr_exec__:NamedTuple(name: String, val: String) at ??
0x10e8db130: __crystal_main at ??
0x10e8ee578: main at ??

Extra Note:

def a_method(*data)
  puts data
end
a_method(1,2,3)
#=> {1,2,3}

def a_method(**data)
  puts data
end
a_method(x: 1, y: 10)
#=> {x: 1, y: 10}

To summarize:

• Tuples are immutable data structure
• Regular tuple is like a frozen array
• You can use splat only with a tuple
• NamedTuple is like a frozen hash
• Double splat can only be used with NamedTuple

• Backend of action cable which is used to provide notifications (pub/sub)
• Queue system used by background workers (Sidekiq, Resque)
• Web Caching
• Session Store – sharing user session across all the load balanced servers
• Fast accessible meta data catalog for your inventory or tool
• Counting – Redis offers a fast method to increment and decrement value. Being an in-memory storage does add

What is a database view?

Making liberal use of views is a key aspect of good SQL database design. Views allow you to encapsulate the details of the structure of your tables, which might change as your application evolves, behind consistent interfaces.  

CREATE VIEW company_manager AS
SELECT id, name, email
FROM  companies
WHERE role='manager';

SELECT * FROM company_managers;

So what is a Materialized view?

1. It’s read-only (pseudo-table) so you can’t update it.
2. You need to refresh the table to get the latest data.
3. While refreshing, it would block other connections to access the existing data from the material view, so you need to make the refresh run concurrently

So why use Materialized views in Rails?

• Capture commonly used joins & filters.
• Push data intensive processing from Ruby to Database.
• Allow fast and live filtering of complex associations or calculation fields.

How do you use it in Rails?

bundle exec rails g migration create_all_time_sales_mat_view

class CreateAllTimesSalesMatView < ActiveRecord::Migration
  def up
    execute <<-SQL
      CREATE MATERIALIZED VIEW all_time_sales_mat_view AS
        SELECT sum(amount) as total_sale,
        DATE_TRUNC('day', invoice_adte) as date_of_sale
      FROM sales
      GROUP BY DATE_TRUNC('day', invoice_adte)
    SQL
  end
  def down
    execute("DROP MATERIALIZED VIEW IF EXISTS all_time_sales_view")
  end
end

class AllTimeSalesMatView < ActiveRecord::Base
  self.table_name = 'all_time_sales_mat_view'
  def readonly?
    true
  end
  def self.refresh
    ActiveRecord::Base.connection.execute('REFRESH MATERIALIZED VIEW CONCURRENTLY all_time_sales_mat_view')
  end
end

AllTimeSalesMatView.select(:date_of_sale)
AllTimeSalesMatView.sum(:total_sale)

Regular
       user     system      total        real
     (976.4ms)  0.020000   0.000000   0.020000 (  0.990258)
MatiView
     (2.3ms)    0.000000   0.010000   0.010000 (  0.012010)

Summarize

Good Points

• Faster to fetch data.
• Capture commonly used joins & filters.
• Push data intensive processing from Ruby to Database.
• Allow fast and live filtering of complex associations or calculation .fields.

Pain Points

• To alter table we need to write SQL
• We will be using more RAM and Storage
• Requires Postgres 9.3 for MatView
• Requires Postgres 9.4 to refresh concurrently
• Can’t have Live data
  • You can fix this by creating your own MatViewTable and updating it with the latest information

References

• https://www.postgresql.org/docs/9.3/static/rules-materializedviews.html
• http://en.wikipedia.org/wiki/Materialized_view
• http://dev.mysql.com/doc/refman/5.7/en/create-view.html
• https://blog.pivotal.io/labs/labs/database-views-performance-rails
• https://www.sitepoint.com/speed-up-with-materialized-views-on-postgresql-and-rails/

• Storing data in JSON and JSONB format
• Generating JSON results from the query itself

Getting Started

How to generate JSON

select row_to_json(users) from users where id = 1;

{"id":1,"email":"hsps@redpanthers.co","encrypted_password":"iwillbecrazytodisplaythat",
"reset_password_token":null,"reset_password_sent_at":null,
"remember_created_at":"2016-11-06T08:39:47.983222",
"sign_in_count":11,"current_sign_in_at":"2016-11-18T11:47:01.946542",
"last_sign_in_at":"2016-11-16T20:46:31.110257",
"current_sign_in_ip":"::1","last_sign_in_ip":"::1",
"created_at":"2016-11-06T08:38:46.193417",
"updated_at":"2016-11-18T11:47:01.956152",
"first_name":"Super","last_name":"Admin","role":3}

select row_to_json(results)
from (
  select id, email from users
) as results

{"id":1,"email":"hsps@redpanthers.co"}

select row_to_json(result)
from (
  select id, email,
    (
      select array_to_json(array_agg(row_to_json(user_projects)))
      from (
        select id, name
        from projects
        where user_id=users.id
        order by created_at asc
      ) user_projects
    ) as projects
  from users
  where id = 1
) result

{"id":1,"email":"hsps@redpanthers.co", "project":["id": 3, "name": "CSnipp"]}

array_to_json(array_agg(row_to_json(user_projects)))

json_agg(user_projects)

json_build_object('foo',1,'bar',2)

{"foo": 1, "bar": 2}

References

require 'irb'
# all the codes before the binding
binding.irb
# all the codes after the binding

bundle exec sidekiq -d

/path/to/rails/app/tmp/pid/sidekiq.pid

pkill -F /path/to/rails/app/tmp/pid/sidekiq.pid

rvm wrapper 2.3.1 systemd bundle