Group items tagged

"HDF (Hierarchical Data Format) technologies are relevant when the data challenges being faced push the limits of what can be addressed by traditional database systems, XML documents, or in-house data formats. Leveraging the powerful HDF products and the expertise of The HDF Group, organizations realize substantial cost savings while solving challenges that seemed intractable using other data management technologies. Many HDF adopters have very large datasets, very fast access requirements, or very complex datasets. Others turn to HDF because it allows them to easily share data across a wide variety of computational platforms using applications written in different programming languages. Some use HDF to take advantage of the many open-source and commercial tools that understand HDF. Similar to XML documents, HDF files are self-describing and allow users to specify complex data relationships and dependencies. In contrast to XML documents, HDF files can contain binary data (in many representations) and allow direct access to parts of the file without first parsing the entire contents. HDF, not surprisingly, allows hierarchical data objects to be expressed in a very natural manner, in contrast to the tables of relational database. Whereas relational databases support tables, HDF supports n-dimensional datasets and each element in the dataset may itself be a complex object. Relational databases offer excellent support for queries based on field matching, but are not well-suited for sequentially processing all records in the database or for subsetting the data based on coordinate-style lookup."

 Ø  The socket library that acts as a concurrency framework.  Ø  Faster than TCP, for clustered products and supercomputing.  Ø  Carries messages across inproc, IPC, TCP, and multicast.  Ø  Connect N-to-N via fanout, pubsub, pipeline, request-reply.  Ø  Asynch I/O for scalable multicore message-passing apps.  Ø  Large and active open source community.  Ø  30+ languages including C, C++, Java, .NET, Python.  Ø  Most OSes including Linux, Windows, OS X.  Ø  LGPL free software with full commercial support from iMatix.

"Syntax highlighting for Neo4j's Cypher query language in SublimeText."

"Scaldi - is Scala dependency injection library. Basically Scala already have everything you need for dependency injection. But still some things can be made easier. Goal of the project is to provide more standard and easy way to make dependency injection in Scala projects consuming power of the Scala language. "

"Faunus is a property graph analytics engine based on Hadoop. A breadth-first version of the graph traversal language Gremlin operates on a vertex-centric property graph data structure. Faunus can be extended with new operations written using MapReduce and Blueprints."

"The Neo4j Scala wrapper library allows you the Neo4j open source graph database through a domain-specific simplified language."

"Sweet.js brings hygienic macros from languages like Scala, Scheme and Rust to JavaScript. "

"Model your domain in the language and style of Domain Driven Design. Implement it using Scala case classes and companion objects. Pass us your subdomain, and we provide the persistence. Persistence concerns, operations and data are abstracted behind an elegant persistence API. We provide you with fully featured repositories for MongoDB and Cassandra. We provide a suite of integration tests to exercise your repositories against a real database, as well as in-memory repositories for other tests."

Rich Hickey discusses simplicity, why it is important, how to achieve it in design and how to recognize its absence in the tools, language constructs and libraries.

"Our project (titled xstream)  concentrated on evaluation of XPath over XML streams. This research area contains multiple challenges resulting  from both the richness  of the language and the requirement of having only a single  pass over the data. We modified and extended one of the known algorithms, TurboXPath  [4], a tree-based IBM algorithm. We also  provide extensive comparative analysis between  TurboXPath and XSQ [5], currently the most advanced of  finite automata (FA)-based algorithms."

"In this paper we propose the TurboXPath path processor, which accepts a language equivalent to a subset of the for-let-where constructs of XQuery over a single document. TurboXPath can be extended to provide full XQuery support or used to augment federated database engines for efficient handling of queries over XML data streams produced by external sources. Internally, TurboXPath uses a tree-shaped path expression with multiple outputs to drive the execution. The result of a query execution is a sequence of tuples of XML fragments matching the output nodes. Based on a streamed execution model, TurboXPath scales up to large documents and has limited memory consumption for increased concurrency"

Scala language git repository @ github.

Reactive-web is a new framework for writing highly interactive and dynamic web applications. It's written in Scala , sits on top of Lift, and uses the Functional Reactive Programming library reactive-core (it's in the same repository). As in GWT, you can code the user interface in the same language as the rest of your application (except in Scala instead of Java), rather than writing JavaScript. Unlike GWT, however, you don't need an extra build step to convert your code to JavaScript. You can easily combine code that runs on the browser with code that runs on the server. And, you can declare dynamic relationships between components, like binding in Flex/JavaFX/etc. (only much more powerful).

"SymbolHound is a search engine that doesn't ignore special characters. This means you can easily search for symbols like &, %, and π. We hope SymbolHound will help programmers find information about their chosen languages and frameworks more easily."

"Welcome to Scala Puzzlers, the collection of Traps, Pitfalls and Corner Cases in the Scala language. Prepare to be surprised, entertained and...well, puzzled! What is presented here is a selection of seemingly simple examples which demonstrate that there's plenty of head-scratching left in Scala. Let your mind be challenged by unexpected and unintuitive behaviour and results and learn something in the process. "

"Shark is a large-scale data warehouse system for Spark designed to be compatible with Apache Hive. It can execute Hive QL queries up to 100 times faster than Hive without any modification to the existing data or queries. Shark supports Hive's query language, metastore, serialization formats, and user-defined functions, providing seamless integration with existing Hive deployments and a familiar, more powerful option for new ones."

"Datomic is a distributed database designed to enable scalable, flexible and intelligent applications, running on next-generation cloud architectures. It does this by: Bringing declarative data manipulation into the application, and the data with it Getting time, process and perception right Process (writes) require coordination Perception (reads) require none The past doesn't change Leveraging immutability, and a sound model of state Datomic has: ACID Transactions Joins A sound data model A logical query language - Datalog Thus, Datomic avoids the compromises and losses of many NoSQL solutions. In addition, it offers flexibility and power over the traditional model in supporting: Hierarchy Multi-valued attributes Minimal schema Reliable operation on unreliable, ephemeral cloud instances Time Datomic avoids manual caching and replication, complex configuration, sharding (automatic or manual), logging, locking, latching and disk management of traditional servers."

"pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language."

"Configuration library for JVM languages. Overview implemented in plain Java with no dependencies extensive test coverage supports files in three formats: Java properties, JSON, and a human-friendly JSON superset merges multiple files across all formats can load from files, URLs, or classpath good support for "nesting" (treat any subtree of the config the same as the whole config) users can override the config with Java system properties, java -Dmyapp.foo.bar=10 supports configuring an app, with its framework and libraries, all from a single file such as application.conf parses duration and size settings, "512k" or "10 seconds" converts types, so if you ask for a boolean and the value is the string "yes", or you ask for a float and the value is an int, it will figure it out. JSON superset features: comments includes substitutions ("foo" : ${bar}, "foo" : Hello ${who}) properties-like notation (a.b=c) less noisy, more lenient syntax substitute environment variables This library limits itself to config files. If you want to load config from a database or something, you would need to write some custom code. The library has nice support for merging configurations so if you build one from a custom source it's easy to merge it in."