Cassandra ppt 2

Sep 14, 20151 like680 views

This document provides instructions for downloading and configuring Apache Cassandra, including ensuring necessary properties are configured in the cassandra.yaml file. It also outlines how to use the Cassandra CQL shell to describe and interact with the cluster, keyspaces and tables. Finally, it mentions the DataStax tools DevCenter and OpsCenter for inserting and analyzing Cassandra data.

Downloading Apache Cassandra
2.0.8
http://planetcassandra.org/cassandra/

Cassandra.yaml
DataStax Enterprise installs: ../cassandra/conf/
In the cassandra.yaml file, the following properties are properly
configured for the cluster that you are importing into:
 cluster_name
 listen_address
 storage_port
 rpc_address
 rpc_port

Cassandra CQL Shell
 Describe cluster, keyspace and table
 Create keyspace
 Create table
 Copy FROM and TO

DataStax DevCenter
http://www.datastax.com/download#dl-devcenter

DataStax DevCenter
 Partition Key and clustering key
 Insert sample data with TTL
 Counter with updates

DataStax OpsCenter
 Dash Board
 Nodes
 Performance Metrics
 Schema

This document summarizes Cassandra, an open source distributed database management system designed to handle large amounts of data across many commodity servers. It discusses Cassandra's history, key features like tunable consistency levels and support for structured and indexed columns. Case studies describe how companies like Digg, Twitter, Facebook and Mahalo use Cassandra to handle terabytes of data and high transaction volumes. The roadmap outlines upcoming releases that will improve features like compaction, management tools, and support for dynamic schema changes.

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The document compares Cassandra and PostgreSQL when deployed at scale. It outlines that Cassandra uses a peer-to-peer and masterless architecture with tunable consistency levels and can scale up and down easily. Cassandra also integrates tightly with Hadoop and offers the CQL query language similar to SQL. The document provides examples of basic SQL commands and their Cassandra equivalents using the CQL language.

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This document introduces Apache Cassandra, a distributed column-oriented NoSQL database. It discusses Cassandra's architecture, data model, query language (CQL), and how to install and run Cassandra. Key points covered include Cassandra's linear scalability, high availability and fault tolerance. The document also demonstrates how to use the nodetool utility and provides guidance on backing up and restoring Cassandra data.

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The database industry has been abuzz over the past year about NoSQL databases. Apache Cassandra, which has quickly emerged as a best-of-breed solution in this space, is used at many companies to achieve unprecedented scale while maintaining streamlined operations. This presentation goes beyond the hype, buzzwords, and rehashed slides and actually presents the attendees with a hands-on, step-by-step tutorial on how to write a Java application on top of Apache Cassandra. It focuses on concepts such as idempotence, tunable consistency, and shared-nothing clusters to help attendees get started with Apache Cassandra quickly while avoiding common pitfalls.

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This document provides an overview and introduction to Cassandra including: - An agenda that outlines the topics covered in the overview including architecture, data modeling differences from RDBMS, and CQL. - Recommended resources for learning more about Cassandra including documentation, video courses, books, and articles. - Requirements that Cassandra aims to meet for database management including scaling, uptime, performance, and cost. - Key aspects of Cassandra including being open source, distributed, decentralized, scalable, fault tolerant, and using a flexible data model. - Examples of large companies that use Cassandra in production including Apple, Netflix, eBay, and others handling large datasets.

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This document provides an introduction to Cassandra, including key details about its history, supported versions, scalability, data model, and use cases. Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers. It provides high availability with no single points of failure and linear scalability across commodity hardware. Cassandra is optimized for fast reads on large datasets based on predefined keys or indexes and is well-suited for applications with heavy write loads like time series data, messaging, and fraud detection.

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Archaic database technologies just don't scale under the always on, distributed demands of modern IOT, mobile and web applications. We'll start this Intro to Cassandra by discussing how its approach is different and why so many awesome companies have migrated from the cold clutches of the relational world into the warm embrace of peer to peer architecture. After this high-level opening discussion, we'll briefly unpack the following: • Cassandra's internal architecture and distribution model • Cassandra's Data Model • Reads and Writes

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Cassandra is a distributed, column-oriented database that scales horizontally and is optimized for writes. It uses consistent hashing to distribute data across nodes and achieve high availability even when nodes join or leave the cluster. Cassandra offers flexible consistency options and tunable replication to balance availability and durability for read and write operations across the distributed database.

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The document summarizes a meetup about Cassandra internals. It provides an agenda that discusses what Cassandra is, its data placement and replication, read and write paths, compaction, and repair. Key concepts covered include Cassandra being decentralized with no single point of failure, its peer-to-peer architecture, and data being eventually consistent. A demo is also included to illustrate gossip, replication, and how data is handled during node failures and recoveries.

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This document provides an overview of the Cassandra NoSQL database. It begins with definitions of Cassandra and discusses its history and origins from projects like Bigtable and Dynamo. The document outlines Cassandra's architecture including its peer-to-peer distributed design, data partitioning, replication, and use of gossip protocols for cluster management. It provides examples of key features like tunable consistency levels and flexible schema design. Finally, it discusses companies that use Cassandra like Facebook and provides performance comparisons with MySQL.

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Apache Cassandra is a free and open source distributed database management system that is highly scalable and designed to manage large amounts of structured data. It provides high availability with no single point of failure. Cassandra uses a decentralized architecture and is optimized for scalability and availability without compromising performance. It distributes data across nodes and data centers and replicates data for fault tolerance.

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This document outlines an online course on Cassandra that covers its key concepts and features. The course contains 8 modules that progress from introductory topics to more advanced ones like integrating Cassandra with Hadoop. It teaches students how to model and query data in Cassandra, configure and maintain Cassandra clusters, and build a sample application. The course includes live classes, recordings, quizzes, assignments, and an online certification exam to help students learn Cassandra.

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This document discusses evaluating Apache Cassandra as a cloud database. It provides an overview of DataStax, the commercial leader in Apache Cassandra. DataStax delivers database products and services based on Cassandra. Cassandra is a free, distributed, high performance, and extremely scalable database that can serve as both a real-time and read-intensive database. The document outlines how Cassandra stacks up against key attributes of a cloud database such as transparent elasticity, scalability, high availability, and more. It encourages readers to download Cassandra to try in their own environments.

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Cassandra ppt 2

1. SKILLWISE-CASSANDRA PPT-II

2. Downloading Apache Cassandra 2.0.8 http://planetcassandra.org/cassandra/

3. Cassandra.yaml DataStax Enterprise installs: ../cassandra/conf/ In the cassandra.yaml file, the following properties are properly configured for the cluster that you are importing into:  cluster_name  listen_address  storage_port  rpc_address  rpc_port

4. Cassandra CQL Shell  Describe cluster, keyspace and table  Create keyspace  Create table  Copy FROM and TO

5. DataStax DevCenter http://www.datastax.com/download#dl-devcenter

6. DataStax DevCenter  Partition Key and clustering key  Insert sample data with TTL  Counter with updates

7. DataStax OpsCenter  Dash Board  Nodes  Performance Metrics  Schema