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Summary - Distributed and big data

Speed up an analytical query with columnar storage.

Summary - Distributed and big data

Distributed SQL: FDW for remote tables, MPP for parallel, columnar for OLAP, SQL on Hadoop for big data, NoSQL for flexible structure. Scale-out design ties them together.

-- FDW -> MPP -> columnar -> Hadoop
-- NoSQL: CAP seçer

Distributed data arrives five ways.

Practice Summary - Distributed and big data

Summary task: create the analytics table as columnar: WITH (format = 'columnar').

Starter code

query.sql
-- summary distributed
CREATE TABLE analytics (id INT, revenue NUMERIC)

Sample solution

query.sql
CREATE TABLE analytics (id INT, revenue NUMERIC) WITH (format = 'columnar');

Expected output

CREATE TABLE

Questions and answers

Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.

1 Distributed foreign table

Question 
CREATE FOREIGN TABLE remote_events (id INT) SERVER ____
Answer 
CREATE FOREIGN TABLE remote_events (id INT) SERVER remote_server

Explanation: remote_server is the right answer.

2 Which workload suits columnar storage?

  • OLAP Correct answer
  • OLTP
  • Both
  • Files

Explanation: Columnar storage suits OLAP workloads.

3 Summary - Distributed and big data: match the terms

Term Meaning
FDW foreign table
MPP parallel
columnar columnar
Hadoop big data

All lessons in Expert

1 Database design

  1. ER model
  2. Cardinality
  3. Surrogate keys
  4. Natural keys
  5. Denormalization
  6. Summary - Design

2 Index tuning

  1. B-tree structure
  2. Covering index
  3. Partial index
  4. Index selectivity
  5. Index maintenance
  6. Summary - Index tuning

3 Query optimizer

  1. What is an optimizer?
  2. Statistics
  3. Cost model
  4. Join strategies
  5. Plan cache
  6. Summary - Optimizer

4 Project: Performance tuning

  1. Scenario design
  2. Reading plans
  3. Adding indexes
  4. Rewriting queries
  5. Comparing results

5 Replication and sharding

  1. What is replication?
  2. Master-slave
  3. Sync vs async
  4. What is sharding?
  5. Shard key
  6. Summary - Replication and sharding

6 Distributed and big data

  1. Distributed queries
  2. MPP
  3. Columnar storage
  4. SQL on Hadoop
  5. SQL vs NoSQL
  6. Summary - Distributed and big data

7 Security and backup

  1. SQL injection
  2. Parameterised queries
  3. Authorisation
  4. Backup
  5. Recovery
  6. Summary - Security and backup

8 Expert final

  1. Design challenge
  2. Optimization challenge
  3. Security challenge
  4. Backup challenge