Saratov open it teach talk. Дамир Яраев: Введение в Apache Cassandra (В ходе презентации Дамир расскажет, когда и почему стоит переходить с проверенных временем реляционных баз данных на ставшие модными в последнее время решения на базе NoSQL. В качестве примера рассмотрит колоночную NoSQL базу данных Apache Cassandra)

1. Created for BigData Community by Dmitry Yaraev
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Apache Cassandra
When and Why

2. Agenda
1. When RDBMS Becomes a Bottleneck
2. Concepts of NoSQL Paradigm
3. Variety of NoSQL Databases
4. Why Apache Cassandra?
5. Essential Use Cases of Cassandra
6. Bad Usage Patterns
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3. What Is Offered by RDBMS
● Mature technology with common standards
● Easy migration from one engine to another
● Data model corresponds to the real world
● Structured Query Language (SQL)
● ACID transactions
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4. Bottlenecked by RDBMS
● Horizontal scalability
● Schema support and migration
● Server and maintenance cost
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5. NoSQL :: History
● First mention in 1998
● Class of distributed databases
● Not Only SQL
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6. NoSQL :: Features
● Simple schema without relations
● Good horizontal scalability
● Combination of two of the following:
○ Consistency
○ Availability
○ Partition Tolerance
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7. NoSQL :: CAP Theorem
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8. NoSQL :: Storage Types
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9. © 2014 Grid Dynamics
Questions?
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10. Cassandra :: What Is It?
● Wide-column distributed data store
● The latest version is 2.1.2 (released this month)
● Proved itself in production (Instagram, Spotify,
eBay and many other big players on IT market)
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11. Cassandra :: Origin
● Originally created in Facebook
● Open-sourced in 2008
● Apache incubator project in early 2009
● Top level Apache project in March 2010
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12. Cassandra :: Features
● High scalability
● Tunable consistency
● Cross-datacenter replication
● Query language (CQL)
● Drivers for a variety of languages
● Lightweight transactions
● Indexing
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13. Cassandra :: Data Types
● Primitive types
● Arbitrary bytes (blob)
● Collections (list, map, set)
● Tuples (tuple)
● User defined
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14. Cassandra :: Data Model
● Keyspace
● ColumnFamily
● Row
● Column
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15. Cassandra :: Data Model
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16. Cassandra :: ColumnFamily
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17. Cassandra :: CQL3
● SQL-like syntax
● Three types of statements
○ data definition statements
○ data manipulation statements
○ data look up statements
● Prepared statements
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18. Cassandra :: Example Queries
CREATE TABLE songs (
id uuid PRIMARY KEY,
title text,
album text,
artist text,
data blob
);
SELECT * FROM songs WHERE artist = ‘Metallica’; -- RETURNS AN ERROR
CREATE INDEX ON songs(artist);
SELECT * FROM songs WHERE artist = ‘Metallica’;
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19. Cassandra :: Data Distribution
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20. Cassandra :: Replication
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21. Cassandra :: Eventual Consistency
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22. Cassandra :: Tunable Consistency
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23. Cassandra :: Consistency Levels
● Defines a condition for successful read/write
operation
● Multiple Options
○ ONE
○ ALL
○ QUORUM,
○ LOCAL_QUORUM
○ SERIAL
○ …
● Can be specified per request
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24. Cassandra :: Consistency (Quorum)
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25. Cassandra :: Consistency (ONE)
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26. Cassandra :: Consistency (ONE)
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27. Cassandra :: Use Cases
● Large data sets and simple scaling
● Perfectly fits for semi-structured data
● Fault tolerance (no SPoF)
● High write throughput
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28. Cassandra :: Limitations
● No good for large blobs ( > 64MB )
● When there are more read operations than
writes ones and low read latency is critical
● ACID transactions
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29. © 2014 Grid Dynamics
Thanks!
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