Apache Cassandra

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==理论基础==
 
==理论基础==
*peer-to-peer 架构基于 Amazon [[Dynamo]]
+
*peer-to-peer、环形架构基于 Amazon [[Dynamo]]
 
*数据存储模型基于 Google [[BigTable]]
 
*数据存储模型基于 Google [[BigTable]]
 
*[http://www.planetcassandra.org/blog/cassandra-daughter-of-dynamo-and-bigtable/ Cassandra: Daughter of Dynamo and BigTable]
 
*[http://www.planetcassandra.org/blog/cassandra-daughter-of-dynamo-and-bigtable/ Cassandra: Daughter of Dynamo and BigTable]
 +
*[[gossip protocol]]
 +
*[[Staged event-driven architecture|SEDA]]
  
 
==主要特性==
 
==主要特性==
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==版本==
 
==版本==
*3.x
+
*[http://docs.huihoo.com/apache/cassandra/4.x/doc/latest/ 4.x]
 +
*3.x:[http://docs.huihoo.com/apache/cassandra/3.9/html/ 3.9], [http://docs.huihoo.com/javadoc/apache/cassandra/3.9/ 3.9 javadoc]
 
*2.x
 
*2.x
 
[http://www.datastax.com/dev/blog/whats-new-in-cassandra-2-2-json-support What’s New in Cassandra 2.2: JSON Support]
 
[http://www.datastax.com/dev/blog/whats-new-in-cassandra-2-2-json-support What’s New in Cassandra 2.2: JSON Support]
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  or cqlsh 1.2.3.4 9042 // ip, port
 
  or cqlsh 1.2.3.4 9042 // ip, port
 
  cqlsh> help
 
  cqlsh> help
 +
cqlsh> describe keyspaces;
 
  cqlsh> use system;
 
  cqlsh> use system;
 
  cqlsh:system> select * from schema_keyspaces; // 所有keyspaces
 
  cqlsh:system> select * from schema_keyspaces; // 所有keyspaces
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     1746 |  john | smith
 
     1746 |  john | smith
  
  (3 rows)
+
  cqlsh:mykeyspace> select now(), uuid(), token() from mykeyspace.users;
 +
 
 +
You have to be logged in and not anonymous to perform this request
 +
vim cassandra.yaml
 +
authenticator: PasswordAuthenticator
 +
创建新用户
 +
cassandra@cqlsh> create role huihoo with superuser = true and login = true and password = 'huihoo';
 +
cassandra@cqlsh> list roles;
  
 
===Tools===
 
===Tools===
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  ---------
 
  ---------
 
   1000000
 
   1000000
 +
cqlsh> describe stress.standard1;
 +
cqlsh> select * from stress.standard1 limit 10;
  
 
===系统信息===
 
===系统信息===
 
  nodetool --host 127.0.0.1 cfstats
 
  nodetool --host 127.0.0.1 cfstats
 +
cqlsh> describe system;
 
  cqlsh> select * from system.batchlog;
 
  cqlsh> select * from system.batchlog;
 
  cqlsh> select * from system.compaction_history;
 
  cqlsh> select * from system.compaction_history;
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  (user type)      com.datastax.driver.core.UDTValue
 
  (user type)      com.datastax.driver.core.UDTValue
 
  (tuple type)    com.datastax.driver.core.TupleValue
 
  (tuple type)    com.datastax.driver.core.TupleValue
 +
 +
==项目==
 +
[https://github.com/topics/cassandra Apache Cassandra Topics]
 +
*[https://github.com/strapdata/elassandra Elassandra] = [[Elasticsearch]] + Apache Cassandra
 +
*[https://github.com/OpenNMS/newts Newts] is a time-series data store based on Apache Cassandra.
  
 
==C++==
 
==C++==
 
[[ScyllaDB]] 是用 [[C++]] 重写的 Apache Cassandra,完全兼容 Cassandra.
 
[[ScyllaDB]] 是用 [[C++]] 重写的 Apache Cassandra,完全兼容 Cassandra.
 +
 +
==.NET==
 +
*[https://github.com/datastax/csharp-driver DataStax C# Driver for Apache Cassandra]
  
 
==Python==
 
==Python==
[https://github.com/rustyrazorblade/python-presentation Python & Cassandra - Best Friends]
+
*[https://github.com/twissandra/twissandra Twissandra]
 +
*[https://github.com/rustyrazorblade/python-presentation Python & Cassandra - Best Friends]
 
  sudo pip install ipython-cql
 
  sudo pip install ipython-cql
 
  sudo pip install virtualenvwrapper
 
  sudo pip install virtualenvwrapper
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==MariaDB==
 
==MariaDB==
[http://www.infoq.com/cn/news/2012/11/Cassandra-SE MariaDB的Cassandra存储引擎],允许[[MariaDB]]通过标准SQL语法使用Cassandra集群。
+
*[http://www.infoq.com/cn/news/2012/11/Cassandra-SE MariaDB的Cassandra存储引擎] 允许[[MariaDB]]通过标准SQL语法使用Cassandra集群。
 +
*[https://mariadb.com/kb/en/mariadb/cassandra/ Cassandra Storage Engine]
  
 
==Docker==
 
==Docker==
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*[https://tobert.github.io/post/2014-07-15-installing-cassandra-spark-stack.html Installing the Cassandra / Spark OSS Stack]
 
*[https://tobert.github.io/post/2014-07-15-installing-cassandra-spark-stack.html Installing the Cassandra / Spark OSS Stack]
  
==[[Apache_Mesos|Mesos]]==
+
==[[Apache Hadoop|Hadoop]]==
[https://github.com/mesosphere/cassandra-mesos Cassandra on Mesos]
+
[https://wiki.apache.org/cassandra/HadoopSupport Hadoop Support]
 +
 
 +
==[[Presto]]==
 +
[https://prestodb.io/docs/current/connector/cassandra.html Cassandra Connector]
 +
 
 +
==集群HA==
 +
*[https://github.com/riptano/ccm CCM (Cassandra Cluster Manager)]
 +
*[https://github.com/mesosphere/cassandra-mesos Cassandra on Mesos]
  
 
==控制台==
 
==控制台==
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*[https://github.com/tbarbugli/cassandra_snapshotter Cassandra Snapshotter]
 
*[https://github.com/tbarbugli/cassandra_snapshotter Cassandra Snapshotter]
 
*[https://github.com/hailocab/ctop CTOP ("Top for Cassandra")]
 
*[https://github.com/hailocab/ctop CTOP ("Top for Cassandra")]
 +
 +
==IDE==
 +
[https://cassandra.apache.org/doc/latest/development/ide.html Building and IDE Integration]
 +
*[https://downloads.datastax.com/#devcenter DataStax DevCenter] 已不再更新维护 [https://github.com/Patipat-Chuensuwannakul/devcenter @ GitHub]
 +
*[https://downloads.datastax.com/#desktop DataStax Desktop]
 +
*[https://downloads.datastax.com/#studio DataStax Studio] Studio only supports DataStax Enterprise clusters. 
 +
$ ./bin/server.sh
 +
http://127.0.0.1:9091
 +
$ pkill -f studio
 +
*[https://hackolade.com Hackolade]
 +
 +
==Operator==
 +
*[https://github.com/instaclustr/cassandra-operator Kubernetes Operator for Cassandra]
  
 
==驱动==
 
==驱动==
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*[https://github.com/Netflix/astyanax Astyanax] is a high level Java client for Apache Cassandra
 
*[https://github.com/Netflix/astyanax Astyanax] is a high level Java client for Apache Cassandra
 
*[https://pypi.python.org/pypi/django-cassandra-engine/ django-cassandra-engine] - the Cassandra backend for [[Django]]
 
*[https://pypi.python.org/pypi/django-cassandra-engine/ django-cassandra-engine] - the Cassandra backend for [[Django]]
 +
*[https://github.com/impetus-opensource/Kundera Kundera]
 +
*pip install cassandra-driver // python
  
 
==厂商==
 
==厂商==
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*[http://docs.huihoo.com/apache/spark/summit/east2015/SSE15-11-Delivering-Meaning-At-High-Velocity-with-Spark-Streaming-Cassandra-Kafka-and-Akka.pdf Delivering Meaning In NearReal Time At High Velocity & Massive Scale]
 
*[http://docs.huihoo.com/apache/spark/summit/east2015/SSE15-11-Delivering-Meaning-At-High-Velocity-with-Spark-Streaming-Cassandra-Kafka-and-Akka.pdf Delivering Meaning In NearReal Time At High Velocity & Massive Scale]
 
*[http://docs.huihoo.com/oreilly/conferences/strataconf/big-data-conference-ny-2013/An-Introduction-to-Real-Time-Analytics-with-Cassandra-and-Hadoop.pdf An Introduction to Real-Time Analytics with Cassandra and Hadoop]
 
*[http://docs.huihoo.com/oreilly/conferences/strataconf/big-data-conference-ny-2013/An-Introduction-to-Real-Time-Analytics-with-Cassandra-and-Hadoop.pdf An Introduction to Real-Time Analytics with Cassandra and Hadoop]
*[http://docs.huihoo.com/apache/cassandra/Cassandra-Data-Modeling-Best-Practices-at-eBay.pdf Cassandra Data Modeling Best Practices at eBay][http://docs.huihoo.com/apache/cassandra/Cassandra-at-eBay.pdf Cassandra at eBay][http://docs.huihoo.com/apache/cassandra/planetcassandra/Cassandra-at-eBay-Scale.pdf Cassandra Scale at eBay]
+
*[http://docs.huihoo.com/apache/cassandra/Cassandra-Data-Modeling-Best-Practices-at-eBay.pdf Cassandra Data Modeling Best Practices at eBay] [http://docs.huihoo.com/apache/cassandra/Cassandra-at-eBay.pdf Cassandra at eBay] [http://docs.huihoo.com/apache/cassandra/planetcassandra/Cassandra-at-eBay-Scale.pdf Cassandra Scale at eBay]
  
 
==图集==
 
==图集==
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image:Datastax-DevCenter.png|DevCenter
 
image:Datastax-DevCenter.png|DevCenter
 
image:recommendation-engine-personalization.png|个性化推荐引擎
 
image:recommendation-engine-personalization.png|个性化推荐引擎
 +
image:RabbitMQ-Storm-Cassandra.png|RabbitMQ-Storm-Cassandra实时分析
 +
image:RabbitMQ-Storm-Esper-Cassandra.png|实时分析集成Esper
 
image:Microservice-platform.png|微服务平台
 
image:Microservice-platform.png|微服务平台
 
image:cassandra-write-path.png|写路径
 
image:cassandra-write-path.png|写路径
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image:cassandra-keyspace-02-multi-dc.png|Keyspace多数据中心
 
image:cassandra-keyspace-02-multi-dc.png|Keyspace多数据中心
 
image:cassandra-and-spark-analysis-data-center.png|Cassandra+Spark分析数据中心
 
image:cassandra-and-spark-analysis-data-center.png|Cassandra+Spark分析数据中心
 +
image:jconsole-cassandra.png|JConsole
 
image:Gartner-Magic-Quadrant-for-Operational-Database-Management-Systems-October-2015.png|Gartner魔力象限
 
image:Gartner-Magic-Quadrant-for-Operational-Database-Management-Systems-October-2015.png|Gartner魔力象限
 +
image:A-simple-hotel-search-system-using-RDBMS.png|RDBMS模型
 +
image:The-hotel-search-represented-with-Cassandra-model.png|Cassandra模型
 +
image:mariadb-cassandra-storage-engine.png|MariaDB存储引擎
 +
image:32-node-raspberry-pi-cassandra-cluster-01.jpg|Cassandra集群
 +
image:32-node-raspberry-pi-cassandra-cluster-04.jpg|Cassandra集群
 +
image:32-node-raspberry-pi-cassandra-cluster-02.jpg|Cassandra集群
 +
image:32-node-raspberry-pi-cassandra-cluster-03.jpg|Cassandra集群
 +
image:Cassandra-Kubernetes-Operator.jpg|K8s运营
 
</gallery>
 
</gallery>
  
 
==链接==
 
==链接==
 
*[http://cassandra.apache.org/ Apache Cassandra官方网站]
 
*[http://cassandra.apache.org/ Apache Cassandra官方网站]
*[http://www.planetcassandra.org/ Planet Cassandra]
+
*[https://github.com/apache/cassandra Cassandra @ GitHub]
 +
*[https://www.datastax.com/blog DataStax Blog]
 
*[http://docs.huihoo.com/apache/cassandra/ Apache Cassandra文档]
 
*[http://docs.huihoo.com/apache/cassandra/ Apache Cassandra文档]
 
*[http://docs.datastax.com/en/ DataStax Cassandra文档]
 
*[http://docs.datastax.com/en/ DataStax Cassandra文档]
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*[http://www.infoq.com/cn/articles/best-practices-cassandra-data-model-design-part2 Cassandra数据模型设计最佳实践(下部)]
 
*[http://www.infoq.com/cn/articles/best-practices-cassandra-data-model-design-part2 Cassandra数据模型设计最佳实践(下部)]
 
*[http://www.planetcassandra.org/blog/the-most-important-thing-to-know-in-cassandra-data-modeling-the-primary-key/ The most important thing to know in Cassandra data modeling: The primary key]
 
*[http://www.planetcassandra.org/blog/the-most-important-thing-to-know-in-cassandra-data-modeling-the-primary-key/ The most important thing to know in Cassandra data modeling: The primary key]
 +
*[http://www.infoq.com/cn/articles/cassandra-2nd-edition-book-review 《Cassandra权威指南》第二版书评及访谈]
  
{{comment}}
+
[[category:database]]
 
+
 
[[category:NoSQL]]
 
[[category:NoSQL]]
 
[[category:java]]
 
[[category:java]]
 
[[category:apache]]
 
[[category:apache]]
 
[[category:facebook]]
 
[[category:facebook]]
 +
[[category:recommender system]]
 +
[[category:huihoo]]

2021年8月20日 (五) 05:17的最后版本

Wikipedia-35x35.png 您可以在Wikipedia上了解到此条目的英文信息 Apache Cassandra Thanks, Wikipedia.

Apache Cassandra是一套开源分布式Key-Value存储系统。它最初由Facebook开发,用于储存特别大的数据。Facebook目前在使用此系统。

Cassandra.png
Datastax.png

目录

[编辑] 理论基础

[编辑] 主要特性

  • 分布式
  • 基于Column的结构化
  • 高度可伸展性

2 nodes can handle 100,000 transactions per second, 4 nodes will support 200,000 transactions/sec and 8 nodes will tackle 400,000 transactions/sec。

Cassandra-supplies-linear-scalability.png

Cassandra的主要特点就是它不是一个数据库,而是由一堆数据库节点共同构成的一个分布式网络服务,对Cassandra 的一个写操作,会被复制到其他节点上去,对Cassandra的读操作,也会被路由到某个节点上面去读取。对于一个Cassandra群集来说,扩展性能是比较简单的事情,只管在群集里面添加节点就可以了。

Cassandra是一个混合型的非关系型数据库,类似于Google的BigTable。其主要功能比 Dynomite(分布式的Key-Value存储系统)更丰富,但支持度却不如文档存储MongoDB(介于关系数据库和非关系数据库之间的开源产品,是非关系数据库当中功能最丰富,最像关系型数据库。支持的数据结构非常松散,是类似JSON的bjson格式,因此可以存储比较复杂的数据类型)Cassandra最初由Facebook开发,后转变成了开源项目。它是一个网络社交云计算方面理想的数据库。以Amazon专有的完全分布式的Dynamo为基础,结合了Google BigTable基于列族(Column Family)的数据模型。P2P去中心化的存储。很多方面都可以称之为Dynamo 2.0。

和其他数据库比较,有几个突出特点:

  • 模式灵活:使用Cassandra,像文档存储,你不必提前解决记录中的字段。你可以在系统运行时随意的添加或移除字段。这是一个惊人的效率提升,特别是在大型部署上。
  • 真正的可扩展性:Cassandra是纯粹意义上的水平扩展。为给集群添加更多容量,可以指向另一台电脑。你不必重启任何进程,改变应用查询,或手动迁移任何数据。
  • 多数据中心识别:你可以调整你的节点布局来避免某一个数据中心起火,一个备用的数据中心将至少有每条记录的完全复制。

一些使Cassandra提高竞争力的其他功能:

  • 范围查询:如果你不喜欢全部的键值查询,则可以设置键的范围来查询。
  • 列表数据结构:在混合模式可以将超级列添加到5维。对于每个用户的索引,这是非常方便的。
  • 分布式写操作:有可以在任何地方任何时间集中读或写任何数据。并且不会有任何单点失败。

[编辑] 版本

What’s New in Cassandra 2.2: JSON Support

  • 1.x

[编辑] 指南

[编辑] OS X

brew install cassandra 
brew info cassandra
cassandra -f
bin/cassandra -f
bin/cqlsh
or cqlsh 1.2.3.4 9042 // ip, port
cqlsh> help
cqlsh> describe keyspaces;
cqlsh> use system;
cqlsh:system> select * from schema_keyspaces; // 所有keyspaces
cqlsh:system> describe schema_keyspaces; // schema_keyspaces所有表和表定义
cqlsh> CREATE KEYSPACE mykeyspace
   ... WITH REPLICATION = { 'class' : 'SimpleStrategy', 'replication_factor' : 1 };
cqlsh> use mykeyspace;
cqlsh:mykeyspace> CREATE TABLE users (
              ... user_id int PRIMARY KEY,
              ... fname text,
              ... lname text
              ... );
cqlsh:mykeyspace> INSERT INTO users (user_id,  fname, lname)
              ... VALUES (1745, 'john', 'smith');
cqlsh:mykeyspace> INSERT INTO users (user_id,  fname, lname)
              ... VALUES (1744, 'john', 'doe');
cqlsh:mykeyspace> INSERT INTO users (user_id,  fname, lname)
              ... VALUES (1746, 'john', 'smith');
cqlsh:mykeyspace> select * from users;
 user_id | fname | lname
---------+-------+-------
    1745 |  john | smith
    1744 |  john |   doe
    1746 |  john | smith
cqlsh:mykeyspace> select now(), uuid(), token() from mykeyspace.users;

You have to be logged in and not anonymous to perform this request

vim cassandra.yaml 
authenticator: PasswordAuthenticator

创建新用户

cassandra@cqlsh> create role huihoo with superuser = true and login = true and password = 'huihoo';
cassandra@cqlsh> list roles;

[编辑] Tools

cassandra-stress tool

cd apache-cassandra-2.1.8/tools/bin
cassandra-stress help -schema
cassandra-stress write n=1000000 // 写100万行
cassandra-stress read n=200000 // 读20万行
cassandra-stress write n=1000000 cl=one -mode native cql3 -schema keyspace="stress" -log file=~/load_1M_rows.log // 写入100万行
cqlsh:mykeyspace> select count(*) from stress.standard1;
 count
---------
 1000000
cqlsh> describe stress.standard1;
cqlsh> select * from stress.standard1 limit 10;

[编辑] 系统信息

nodetool --host 127.0.0.1 cfstats
cqlsh> describe system;
cqlsh> select * from system.batchlog;
cqlsh> select * from system.compaction_history;
cqlsh> select * from system.compactions_in_progress;
cqlsh> select * from system.hints;
cqlsh> select * from system.local;
cqlsh> select * from system.peers;
cqlsh> select * from system.peer_events;
cqlsh> select * from system.range_xfers;
cqlsh> select * from system.sstable_activity;
cqlsh> select * from system.schema_columnfamilies;
cqlsh> select * from system.schema_columns;
cqlsh> select * from system.schema_triggers;
cqlsh> select * from system.schema_usertypes;
cqlsh> select * from system.size_estimates;
cqlsh> select * from system.schema_keyspaces;
cqlsh> select * from mykeyspace.users;
cqlsh> select * from system_traces.sessions;
cqlsh> select * from system_traces.events;

[编辑] CQL

CQL and Java type comparison

CQL              Java
===              ====
boolean          java.lang.Boolean
int              java.lang.Integer
bigint           java.lang.Long
float            java.lang.Float
double           java.lang.Double
inet             java.net.InetAddress
text             java.lang.String
ascii            java.lang.String
timestamp        java.util.Date
uuid             java.util.UUID
timeuuid         java.util.UUID
varint           java.math.BigInteger
decimal          java.math.BigDecimal
blob             java.nio.ByteBuffer
list<E>          java.util.List<E>      where E is also a type from this list
set<E>           java.util.Set<E>       where E is also a type from this list
map<K,V>         java.util.Map<K,V>     where K and V is also a types from this list
(user type)      com.datastax.driver.core.UDTValue
(tuple type)     com.datastax.driver.core.TupleValue

[编辑] 项目

Apache Cassandra Topics

[编辑] C++

ScyllaDB 是用 C++ 重写的 Apache Cassandra,完全兼容 Cassandra.

[编辑] .NET

[编辑] Python

sudo pip install ipython-cql
sudo pip install virtualenvwrapper
source /usr/local/bin/virtualenvwrapper.sh
git clone https://github.com/rustyrazorblade/python-presentation
cd python-presentation
mkvirtualenv tutorial
pip install -r requirements.txt
ipython notebook

[编辑] MariaDB

[编辑] Docker

[编辑] Spark

[编辑] Hadoop

Hadoop Support

[编辑] Presto

Cassandra Connector

[编辑] 集群HA

[编辑] 控制台

[编辑] IDE

Building and IDE Integration

$ ./bin/server.sh
http://127.0.0.1:9091
$ pkill -f studio

[编辑] Operator

[编辑] 驱动

[编辑] 厂商

[编辑] 案例

目前,Cassandra对于Netflix而言是首选数据库,因为它们几乎满足了Netflix的所有需求。Netflix已经将95%的数据存储在Cassandra上,包括客户账户信息、影片评分、影片元数据、影片书签和日志等。Netflix在750多个节点上运行着50多个Cassandra集群。高峰时,Netflix每秒要处理50,000多个读取和100,000写入操作。Netflix平均每天要处理21亿次的读取与43亿次的写入操作。

[编辑] 迁移

数据库迁移

[编辑] 文档

[编辑] 图集

[编辑] 链接

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