The breakup

Logically Sharding a Growing PostgreSQL Database

The Breakup

Introductions

Students hate us.

Introductions

Turnitin.com

Samantha: database

@mzsamantha

Fred: code

@phredmoyer

The Seven Stages Of Grief Scaling

1. Shock and Denial2. Pain and Guilt3. Anger and

Bargaining4. Depression &

Reflection5. The Upward Turn6. Reconstruction7. Acceptance and

Hope

The Seven Stages Of Grief Scaling

1. Shock and Denial2. Pain and Guilt3. Anger and

Bargaining4. Depression &

Reflection5. The Upward Turn6. Reconstruction7. Acceptance and

Hope

1. Monolithic Scaling 2. Hardware is

Expensive3. If We Do It This

Way...4. We Are So *%@#!&5. Down To 150 Bugs!6. Release Day7. Beer & Therapy

(beerapy?)

The Problem

● The ability to efficiently backup and restore

● The amount of ram required to keep indexes in memory

● Resource contention causing query planner to make sub-optimal choices.

● Aged data extending query resources and execution time

● Overlap in existing ID spaces

● No account crossover between shards. I.E. Tii-UK and Tii require separate accounts.

Stage 2: Options

● Account based shardingo Difficult to split account usage evenly across shards.

● Geographical based shardingo Currently have one geographical shard (UK).o Added deployment, poor resource utilization.

● Oracle RAC ($$$)o Oracle OpenWorld is Sunday in SF. No bacon there.

● Horizontal shardingo Move fast growing tables to separate physical hosts.o Break relational constraints.o Good path to a service oriented architecture node.

Stage 2: Options

Why Did We Discuss All That Before Phase 1?

Stage 2: Options

Objective Expertise.Please Step Away From the Application.

Triage

What is going to kill us first?

Stage 1: DiagnoseTa

ble

siz

e in

Gig

s

Stage 1: Diagnose

Database size: 507 GB

m_object_paper: 94 GB

gm3_mark: 71 GB

m_object: 53 GB

m_report_stats: 35 GB

Four tables account for half the bulk of the entire database.

Stage 1: Diagnose

What About Table Sharding?

Stage 2: Options

Three Part Two Year Proposal: Short, Mid, and Long term Goals.

Short: 3 MonthsQuery Partition and Refactor

Removal of ‘Leaf Service’: Marks

Stage 2: Options


Mid: 9 MonthsID Reconciliation Between Shards

Table Partitioning

Stage 2: Options


Long: 12 MonthsCreate DAL

Removal of Large TablesGlobal Statistics and Reporting

Stage 2: Options

Short Term: 12 Months LaterI do not think it means what you think it means.

Stage 3: Scoping The Solution - Database

Main

Marks


Data Up Approach:

Start with the schemaIsolate direct links

Slow, Tedious, and Painful


Foreign-key constraints:

"$1" FOREIGN KEY (source) REFERENCES m_object(id)

"$2" FOREIGN KEY (reader) REFERENCES m_user(id)

"m_dg_read_pm_review_set_fkey" FOREIGN KEY (pm_review_set) REFERENCES pm_review_set(id)

Referenced by:

TABLE "gm_mark" CONSTRAINT "$1" FOREIGN KEY (read) REFERENCES m_dg_read(id)

TABLE "erater_read_filter" CONSTRAINT "erater_read_filter_read_fkey" FOREIGN KEY (read) REFERENCES m_dg_read(id) ON DELETE CASCADE

TABLE "gm3_mark" CONSTRAINT "gm3_mark_read_fkey" FOREIGN KEY (read) REFERENCES m_dg_read(id) ON DELETE CASCADE

TABLE "gm3_rubric_scoring" CONSTRAINT "gm3_rubric_scoring_read_fkey" FOREIGN KEY (read) REFERENCES m_dg_read(id)

TABLE "r_mark_criterion" CONSTRAINT "mark_criterion_read_fkey" FOREIGN KEY (read) REFERENCES m_dg_read(id) ON DELETE CASCADE

TABLE "pm_review" CONSTRAINT "pm_review_id_fkey" FOREIGN KEY (id) REFERENCES m_dg_read(id)

TABLE "r_read_audio" CONSTRAINT "r_read_audio_read_id_fkey" FOREIGN KEY (read_id) REFERENCES m_dg_read(id)


Original: 236 tablesNew main database (192 tables)New marks database (40 tables)

Stage 3: Scoping The Solution - Code

Option 1 - Data Access Layer (DAL)

o Separate codebase encapsulating new set of tables

o Written in Golang, an HTTP based REST service

o Avoids carrying forward existing technical debt

o Requires detailed knowledge of existing product features

o Unit tests are very helpful, but coverage is never 100%

o 14 years of business logic (dark matter)

o In long lived web apps, tribal knowledge is authoritative

Stage 3: Scoping The Solution - Code

Option 2 - Add additional database handles to new db

o Perceived as a safer approach (deciding factor,

known risks).

o Requires paying interest on existing technical debt.

o Refactoring is less risky than rewriting.

o Take advantage of existing business logic and tribal

knowledge.

o Preserve sacred cows.

Stage 3: Scoping The Solution - Hardware

"We can use smaller hardware because we are splitting off part of the database"

➢ This is somewhat of a fallacy➢ You might need smaller storage➢ You might need slightly less CPU➢ Stick with close to the same amount of RAM

Stage 4: Implementation - Rollback

S: “What if this fails?”

F: “We Rollback the code, restore the database,

and look for new jobs.”


Q: How do you bifurcate a database and

rollback without data loss?

A: Slony.


Timelines matter. Prepare in advance.

Split Replication Well In Advance.

Test Process, Then Test It Again.

Stage 4: Implementation - Archaeology

● What is this table? That service doesn’t exist

anymore?○ Let’s Drop it!

● What’s that table? It’s an old version still in

use?○ Let’s Drop it!

● What’s that one over there?○ Let’s Drop it!


Wait… old version still in use?


● Fourteen years of application development.

● Five major codebases, dozens of support utilities.

● Hundreds of codepoints for database connections.

● A dozen different ORMs.

● Dynamically generated SQL joining tables.

● Technical debt (code with high maintenance costs).

● Best practices of 10 years ago are now liabilities.

How do you change all of the electrical sockets in an

(old) office building?



EMPATHY


EMPATHYput yourself in the mind of the

author


James left 8 years ago. The elevator is in old building.They tore down the old building to build a Target.

# this code is critical to our workflow, don’t remove it!!# for details talk to jamesb <> who sits near the elevator# $foo = $object->flocculate( key => $cfg->secret_key );# return $foo;return;


Bob is still here though. Bob is a little particular about his code though (we are all to some degree).

Now you’re in there meddling with Bob’s code. How would you feel if you were Bob?

A little empathy goes a long way towards getting Bob to help you get his code ported to the new dual database schema.

Stage 4: Implementation - Queries

main database - marks databaseSELECT count(m.*) FROM gm3_mark m, gm3_qm_template qmtWHERE m.read IN

(SELECT dgr.id FROM m_dg_read dgrJOIN m_object_paper mop ON (mop.id =

dgr.source AND mop.owner = ?)JOIN m_assignment ma ON (ma.id =

mop.assignment AND ma.class = ?) WHERE reader = ?)

AND m.qm_template = qmt.id AND qmt.id = ?

Main Database - grab ids to pass to marks database.

SELECT p.id FROM m_object_paper pJOIN m_assignment a ON a.id = p.assignmentWHERE a.class = ? AND p.owner = ?



Marks database - pass former FK ids to an IN clause.

SELECT count(m.*) FROM gm3_mark m JOIN gm3_qm_template qmt ON qmt.id = m.qm_template JOIN m_dg_read dgr ON dgr.id = m.read WHERE dgr.source IN (?, ?, ?) AND qmt.id = ? AND dgr.reader = ?

Stage 4: Implementation - Transactions

Single database transactions are easy.eval { $db->do(“INSERT INTO foo (name) VALUES (‘bar’)”); $id = $db->do(“SELECT CURRVAL(‘foo’)”); $db->do(“INSERT INTO fee (foo_id) VALUES ($id)”);};if ($@) { # catch exception $db->rollback; # roll transaction back} else { $db->commit; # commit transaction}


Dual database transactions are harder.

eval { # insert into foo in main db, grab last value $main_db->do(“INSERT INTO foo VALUES (‘bar’)”); $foo_id = $main_db->do(“SELECT CURRVAL(‘foo’)”);

# insert foo id into marks db, grab last value $marks_db->do(“INSERT INTO fee VALUES ($id)”); $fee_id = $main_db->do(“SELECT CURRVAL(‘fee’)”);};


Roll back both handles on exception, commit both on success.

if ($@) { # catch exception $main_db->rollback; # roll main_db back $marks_db->rollback; # roll marks_db back} else { $main_db->commit; # commit main_db $marks_db->commit; # commit marks_db}


What if the commit fails?if ($@) { # catch exception $main_db->rollback; # roll main_db back $marks_db->rollback; # roll marks_db back} else { eval { $main_db->commit }; if ($@) { $main_db->rollback; $marks_db->rollback; } eval { $marks_db->commit }; ...


CAP (Brewer’s Law)


Consistency or Availability?


9 out of 10 users prefer availability

So does customer support.You can fix consistency.

Stage 4: Implementation - ORMs

ORMs are full of pain

● They hide away db connection details.

● They make it hard to break models apart.

● They make writing code easy…

● But debugging is much more difficult.

Stage 4: Implementation - ORMs

ORMs are full of painBack in my day we used SQL, and we liked it.

$classes = $c->classes->search( $select_hash, { '+select' => 'source.id', '+as' => 'src_id', 'join' => [ { 'user_rights_class' => { 'user_role' => 'owner' } }, 'source' ], 'rows' => 200, 'page' => 1 } );

Stage 4: Implementation - Juggling

Talking to two databases is easy, right?


Talking to two databases is easy, right?

Not as easy as it seems.


Main database - Marks database

Are you talking to me?


Main database - Marks database

I think he was talking to me.

Stage 4: Implementation - Config

● Main Database: One master, two slaves (2)

● Marks Database: One master, two slaves (2)

● ASP application: write user, read only user (2)

● Catalyst Application: write user, read only user (2)

● REST Application: write user, read only user (2)

● dev, qa, staging, production, sandbox, uk (6)


● Database hosts and users: 2*5 = 10

● Stages: 10 * 6 = 60

● Config managed in version control, no discovery.

● Config deployed via RPM with application.

● Get one wrong? Start all over again.

● Configuration is full of pain and suffering.


Yes, we are moving to Chef.

Stage 4: Implementation - Tech Debt

How much tech debtdo you have?


How much tech debtdo you have?

More than you think.


How much of it will you have to deal with?


How much of it will you have to deal with?

More than you think.


Our legacy app:

● 5 ORMs

● No unit tests (many integration tests)

● Two template frameworks

● 9 different log files

● Code is generally pretty readable!

Stage 5: Release

Planned 8 hour Maintenance Window15 People + support

2.5 Hours Main Service1.5 Hours UK

2 Hours Sandbox + Cat Videos

Stage 5: Release

Stage 6: Cleanup

Patch Flavors:How Did That Get there?

That’s a bug.It worked fine in dev.

Stage 6: Cleanup

“Sometimes the query planner does dumb things”

o People forget why you embarked on this effort.

o People forget the successes and risk mitigation.

o People won’t forget the visceral reactions to

service degradations.

Stage 6: Cleanup

How to bring your site to a halt:

1.Start transaction to database 12.Start transaction to database 23.Wait for database 1 to finish

Stage 6: Cleanup

PANIC

Stage 6: Cleanup

Gone in 60 seconds

Stage 6: Cleanup

Stage 6: Cleanup

Where Do We Golang From here?

Back To Plan A.

Most of the heavy lifting is done.

“The first split is the hardest” - Some Guy Here

The End

So long SurgeCon!

And thanks for the bacon.

The breakup

Technology

Transcript of The breakup