Group items tagged

"Apache Phoenix is a SQL skin over HBase delivered as a client-embedded JDBC driver targeting low latency queries over HBase data. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. The table metadata is stored in an HBase table and versioned, such that snapshot queries over prior versions will automatically use the correct schema. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows. "

"Apache Phoenix is a SQL skin over HBase delivered as a client-embedded JDBC driver targeting low latency queries over HBase data. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. The table metadata is stored in an HBase table and versioned, such that snapshot queries over prior versions will automatically use the correct schema. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows."

"HPaste unlocks the rich functionality of HBase for a Scala audience. In so doing, it attempts to achieve the following goals: Provide a strong, clear syntax for querying and filtration Perform as fast as possible while maintaining idiomatic Scala client code -- the abstractions should not show up in a profiler! Re-articulate HBase's data structures rather than force it into an ORM-style atmosphere. A rich set of base classes for writing MapReduce jobs in hadoop against HBase tables. Provide a maximum amount of code re-use between general Hbase client usage, and operation from within a MapReduce job. Use Scala's type system to its advantage--the compiler should verify the integrity of the schema. Be a verbose DSL--minimize boilerplate code, but be human readable!"

"Twitter's collection of LZO and Protocol Buffer-related Hadoop, Pig, Hive, and HBase code."

Para cosas que no necesitan de sincronicidad, como un agregador de eventos de logging o un registrador de estadísticas de ambiente de ejecución, esta librería cliente de HBase parece mucho mucho mejor que el cliente propio.

"Apache Hama is a pure BSP (Bulk Synchronous Parallel) computing framework on top of HDFS (Hadoop Distributed File System) for massive scientific computations such as matrix, graph and network algorithms. Today, many practical data processing applications require a more flexible programming abstraction model that is compatible to run on highly scalable and massive data systems (e.g., HDFS, HBase, etc). A message passing paradigm beyond Map-Reduce framework would increase its flexibility in its communication capability. Bulk Synchronous Parallel (BSP) model fills the bill appropriately. Some of its significant advantages over MapReduce and MPI are: * Supports message passing paradigm style of application development * Provides a flexible, simple, and easy-to-use small APIs * Enables to perform better than MPI for communication-intensive applications * Guarantees impossibility of deadlocks or collisions in the communication mechanisms"

"The Cloudera Development Kit, or CDK for short, is a set of libraries, tools, examples, and documentation focused on making it easier to build systems on top of the Hadoop ecosystem. The goals of the CDK are: Codify expert patterns and practices for building data-oriented systems and applications. Let developers focus on business logic, not plumbing or infrastructure. Provide smart defaults for platform choices. Support piecemeal adoption via loosely-coupled modules."

"The idea behind Kundera is to make working with NoSQL Databases drop-dead simple and fun. Kundera is being developed with following objectives: To make working with NoSQL as simple as working with SQL To serve as JPA Compliant mapping solution for NoSQL Datastores. To help developers, forget the complexity of NoSQL stores and focus on Domain Model. To make switching across data-stores as easy as changing a configuration. "

Excelente artículo. Habría que distribuirlo por unas cuantas oficinas.

"The Cloudera Connector for Qlikview enables your Enterprise's power users to access Hadoop data through the Qlikview 11.2. The driver achieves this by translating Open Database Connectivity (ODBC) calls from Qlikview into HiveQL queries. The driver supports CDH 4.1."