Beginning Apache Cassandra development

__Beginning Apache Cassandra Development__ introduces you to one of the most robust and best-performing NoSQL database platforms on the planet. Apache Cassandra is a document database following the JSON document model. It is specifically designed to manage large amounts of data across many commodity servers without there being any single point of failure. This design approach makes Apache Cassandra a robust and easy-to-implement platform when high availability is needed. Apache Cassandra can be used by developers in Java, PHP, Python, and JavaScript—the primary and most commonly used languages. In __Beginning Apache Cassandra Development__, author and Cassandra expert Vivek Mishra takes you through using Apache Cassandra from each of these primary languages. Mishra also covers the Cassandra Query Language (CQL), the Apache Cassandra analog to SQL. You'll learn to develop applications sourcing data from Cassandra, query that data, and deliver it at speed to your application's users. Cassandra is one of the leading NoSQL databases, meaning you get unparalleled throughput and performance without the sort of processing overhead that comes with traditional proprietary databases. __Beginning Apache Cassandra Development__ will therefore help you create applications that generate search results quickly, stand up to high levels of demand, scale as your user base grows, ensure operational simplicity, and—not least—provide delightful user experiences. Machine generated contents note: Introducing NoSQL -- NoSQL Ecosystem -- CAP Theorem -- Budding Schema -- Scalability -- Identifying the Big Data Problem -- Introducing Cassandra -- Distributed Databases -- Peer-to-Peer Design -- Configurable Data Consistency -- Cassandra Query Language (CQL) -- Installing Cassandra -- Logging in Cassandra -- Application Logging Options -- Changing Log Properties -- Managing Logs via JConsole -- Commit Log Archival -- Configuring Replication and Data Center -- LocalStrategy -- NetworkTopologyStrategy -- SimpleStrategy -- Cassandra Multiple Node Configuration -- Summary -- Introducing Data Modeling -- Data Types -- Dynamic Columns -- Dynamic Columns via Thrift -- Dynamic Columns via cqlsh Using Map Support -- Dynamic Columns via cqlsh Using Set Support -- Secondary Indexes -- CQL3 and Thrift Interoperability -- Changing Data Types -- Thrift Way -- CQL3 Way -- Counter Column -- Counter Column with and without replicate_on_write -- Play with Counter Columns -- Data Modeling Tips -- Summary -- Indexes -- Clustered Indexes vs. Non-Clustered Indexes -- Index Distribution -- Indexing in Cassandra -- Secondary Indexes -- Composite Columns -- Allow Filtering -- Expiring Columns -- Default TTL -- Data Partitioning -- What's New in Cassandra 2.0 -- Compare and Set -- Secondary Index over Composite Columns -- Conditional DDL -- Summary -- Authentication and Authorization -- system and system_auth Keyspaces -- Managing User Permissions -- Accessing system_auth with AllowAllAuthorizer -- Preparing Server Certificates -- Connecting with SSL Encryption -- Connecting via Cassandra-cli -- Connecting via cqlsh -- Connecting via the Cassandra Thrift Client -- Summary -- Batch Processing and MapReduce -- Apache Hadoop -- HDFS -- MapReduce -- Read and Store Tweets into HDFS -- Cassandra MapReduce Integration -- Reading Tweets from HDFS and Storing Count Results into Cassandra -- Cassandra In and Cassandra Out -- Stream or Real-lime Analytics -- Summary -- Data Migration and Analytics -- Apache Pig -- Setup and Installation -- Understanding Pig -- Counting Tweets -- Pig with Cassandra -- Apache Hive -- Setup and Configuration -- Understanding UDF, UDAF, and UDTF -- Hive Tables -- Local FS Data Loading -- HDFS Data Loading -- Hive External Table -- Hive with Cassandra -- Data Migration -- In the Traditional Way -- Apache Sqoop -- Sqoop with Cassandra -- Summary -- Introduction to Graphs -- Simple and Nonsimple Graphs -- Directed and Undirected Graphs -- Cyclic and Acyclic Graphs -- Open Source Software for Graphs -- Graph Frameworks: TinkerPop -- Graph as a Database -- Titan Graph Databases -- Basic Concepts -- Setup and Installation -- Command-line Tools and Clients -- Titan with Cassandra -- Titan Java API -- Cassandra for Backend Storage -- Use Cases -- Summary -- Understanding the Key Performance Indicators -- CPU and Memory Utilization -- Heavy Read/Write Throughput and Latency -- Logical and Physical Reads -- Cassandra Configuration -- Data Caches -- Bloom Filters -- Off-Heap vs. On-Heap -- Cassandra Stress Testing -- Write Mode -- Read Mode -- Monitoring -- Compaction Strategy -- Yahoo Cloud Serving Benchmarking -- Summary -- Adding Nodes to Cassandra Cluster -- Replacing a Dead Node -- Data Backup and Restoration -- Using nodetool snapshot and sstableloader -- Using nodetool refresh -- Using clearsnapshot -- Cassandra Monitoring Tools -- Helenos -- DataStax DevCenter and OpsCenter -- Summary -- Cassandra nodetool Utility -- Ring Management -- Schema Management -- JSONifying Data -- Exporting Data to JSON Files with sstable2json -- Importing JSON Data with json2sstable -- Cassandra Bulk Loading -- Summary -- Cassandra 2.1 -- User-Defined Types -- Frozen Types -- Indexing on Collection Attributes -- Upgrading Cassandra Versions -- Backward Compatibility -- Performing an Upgrade with a Rolling Restart -- Troubleshooting Cassandra -- Too Many Open Files -- Stack Size Limit -- Out of Memory Errors -- Too Much Garbage Collection Activity -- Road Ahead with Cassandra -- Summary -- References. Annotation Beginning Apache Cassandra Development introduces you to one of the most robust and best-performing NoSQL database platforms on the planet. Apache Cassandra is a document database following the JSON document model. It is specifically designed to manage large amounts of data across many commodity servers without there being any single point of failure. This design approach makes Apache Cassandra a robust and easy-to-implement platform when high availability is needed. Apache Cassandra can be used by developers in Java, PHP, Python, and JavaScript the primary and most commonly used languages. In Beginning Apache Cassandra Development, author and Cassandra expert Vivek Mishra takes you through using Apache Cassandra from each of these primary languages. Mishra also covers the Cassandra Query Language (CQL), the Apache Cassandra analog to SQL. You'll learn to develop applications sourcing data from Cassandra, query that data, and deliver it at speed to your application's users. Cassandra is one of the leading NoSQL databases, meaning you get unparalleled throughput and performance without the sort of processing overhead that comes with traditional proprietary databases. Beginning Apache Cassandra Development will therefore help you create applications that generate search results quickly, stand up to high levels of demand, scale as your user base grows, ensure operational simplicity, and not least provide delightful user experiences. What you'll learn Configure Apache Cassandra clustersModel your data for high throughputImplement MapReduce algorithmsRun Hive and Pig queries over CassandraQuery with the Cassandra Query LanguageBuild graph-based solutions with Cassandra TitanBack up your data and restore when neededEncrypt and secure your data Who this book is forBeginning Apache Cassandra Development is aimed at developers wanting a high-performing and highly-available database from which to serve large amounts of data at speed to application users. The book is especially suited toward developers working in Java, PHP, Python, and JavaScript who are interested in a NoSQL solution." Apache Cassandra is a document database following the JSON document model and is specifically designed to manage large amounts of data across many commodity servers without there being any single point of failure. This design approach makes Apache Cassandra a robust and easy-to-implement platform when high availability is needed. You'll learn how to: configure Apache Cassandra clusters; model your data for high throughput; implement MapReduce algorithms; run Hive and Pig queries over Cassandra; query with the Cassandra Query Language; build graph-based solutions with Cassandra Titan; back up your data and restore when needed; and encrypt and secure your data. -- Counter Column with and without replicate_on_writePlay with Counter Columns; Data Modeling Tips; Summary; Chapter 3: Indexes and Composite Columns; Indexes; Clustered Indexes vs. Non-Clustered Indexes; Index Distribution; Indexing in Cassandra; Secondary Indexes; Composite Columns; Allow Filtering; Expiring Columns; Default TTL; Data Partitioning; Changing Partitioners; Data Colocation; Cassandra Writes; Cassandra Reads; What's New in Cassandra 2.0; Compare and Set; Algorithm; Using CAS; Secondary Index over Composite Columns; Conditional DDL; Summary; Chapter 4: Cassandra Data Security Archive_ commandrestore_command; Configuring Replication and Data Center; LocalStrategy; NetworkTopologyStrategy; SimpleStrategy; Cassandra Multiple Node Configuration; Configuring Multiple Nodes over a Single Machine; Configuring Multiple Nodes over Amazon EC2; Summary; Chapter 2: Cassandra Data Modeling; Introducing Data Modeling; Data Types; Dynamic Columns; Dynamic Columns via Thrift; Dynamic Columns via cqlsh Using Map Support; Dynamic Columns via cqlsh Using Set Support; Secondary Indexes; CQL3 and Thrift Interoperability; Changing Data Types; Thrift Way; CQL3 Way; Counter Column Cassandra MapReduce IntegrationReading Tweets from HDFS and Storing Count Results into Cassandra; The Thrift Way; The CQL3 Way; Cassandra In and Cassandra Out; Stream or Real-Time Analytics; Summary; Chapter 6: Data Migration and Analytics; Data Migration and Analytics; Apache Pig; Setup and Installation; Understanding Pig; Pig Execution Modes; Local Mode; MapReduce Mode; Data Types; Simple Data Types; Complex Data Types; PigStorage; LOAD; STORE; FILTER; FOREACH; TOTUPLE; Counting Tweets; Pig with Cassandra; Data Import; Loading Sata with timeuuid; Apache Hive; Setup and Configuration Authentication and Authorizationsystem and system_auth Keyspaces; The system Keyspace Is Unmodifiable; Accessing system_auth Keyspace with Authentication Enabled; Managing User Permissions; Accessing system_auth with AllowAllAuthorizer; Preparing Server Certificates; Connecting with SSL Encryption; Connecting via Cassandra-cli; Connecting via cqlsh; Connecting via the Cassandra Thrift Client; Summary; Chapter 5: MapReduce with Cassandra; Batch Processing and MapReduce; Apache Hadoop; HDFS; MapReduce; Read and Store Tweets into HDFS; Reading Tweets; Storing Tweets into HDFS