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In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

Welcome to the Blazegraph/TinkerPop3 project. The TP3 implementation has some significant differences from the TP2 version. The data model has been changed to use RDF*, an RDF reification framework described here: https://wiki.blazegraph.com/wiki/index.php/Reification_Done_Right. The concept behind blazegraph-gremlin is that property graph (PG) data can be loaded and accessed via the TinkerPop3 API, but underneath the hood the data will be stored as RDF using the PG data model described in this document. Once PG data has been loaded you can interact with it just like you would interact with ordinary RDF - you can run SPARQL queries or interact with the data via the SAIL API. It just works. The PG data model is also customizable via a round-tripping interface called the BlazeValueFactory, also described in detail in this document.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

Spring JdbcTemplate did very convient and useful, but it also has some disadvantages or in another word “inconvenient”. For example, you can’t just pass an object and tell JdbcTemplate to turn it into a sql and save to database just like hibernate does. Alright, you may say “JdbcTemplate doesn’t need you to write hbm.xml , so it’s understandable”. But is it true that this thing is impossible to achieve? And also you know JdbcTemplate can auto turn the result of a query to a list of persistent object a.k.a PO, but when you want to do this you will meet a problem: “How to ?”.Because you can’t find any function of JdbcTemplate to pass a sql and a PO class as we expected. After you google for it, you’ve been told you can create a BeanPropertyRowMapper to deal with this. But isn’t it could be more easier? Based on those questions I create JdbcTemplateTool which can provide these features.

GroupDocs.Viewer is an online document viewer that lets you read documents in your browser, regardless of whether you have the software that they were created in. You can view many types to word processing documents (DOC, DOCX, TXT, RTF, ODT), presentations (PPT, PPTX), spreadsheets (XLS, XLSX), portable files (PDF), and image files (JPG, BMP, GIF, TIFF). For each file, you get a high-fidelity rendering, showing the document just as it would if you opened it in the software it was created in. Layout and formatting is retained and you see an exact copy of the original. GroupDocs.Viewer lets you really read the document. You can search text documents, copy text and even embed the document – GroupDocs.Viewer and all - in a web page. You can print or download the file from GroupDocs.Viewer if you need to work with it offline.

The project provides an implementation of REPOSITORY PATTERN using HIBERNATE for data access. The goal of this project is to provide an EASY TO USE API that allows to write most of CRUD operations you need in development of end user applications in ONE LINE OF CODE even for developers who are unfamiliar with Hibernate. We provide a well tested set of CRUD operations which were assembled in more than 4 years of refactoring of projects of our clients. Instead of writing same code over and over again we encourage you to try this API on your own project and see how many lines of code YOU can replace with JUST ONE LINE.

YET ANOTHER IMPLEMENTATION OF LEVENSHTEIN DISTANCE GenericLevenshtein is an implementation of Minimum Edit Distance, also called Levenshtein Distance, written by Ramon Ziai and Niels Ott. This algorithm is very popular and it is often used to compute the similarity of strings. The difference in the presented implementation is that it can operate on sequences of any Java object implementing equals(Object). So no matter if you want to compare genome sequences or sequences of numbers, or just strings, here you go! Furthermore, the costs of the replace, insert, and delete operations can be customized by implementing the simple WeightCalculator<T> interface. In that case it is not a requirement to rely on equals(Object) as your implementation can do whatever you like it to do in oder to compare objects.

The project provides an implementation of REPOSITORY PATTERN using HIBERNATE for data access. The a goal of this project is to provide an EASY TO USE API that allows to write most of CRUD operations you will need in development of end user applications in ONE LINE OF CODE even for developers who are unfamiliar with Hibernate. We provide a well tested set of CRUD operations which were assembled in more than 4 years of refactoring of projects of our clients. Instead of writing same code over and over again we encourage you to try this API on your own project and see how many lines of code YOU can replace with JUST ONE LINE.

Geronimo integration testsuite. This contains 2 profiles, default and child. The default profile is used by the top level suites directly under this. The child profile is used by the test poms under the suites. This pom defines the basic dependencies needed by most suites. The start-selenium, start-server, invoke, and stop-server goals are globally configured here in the pluginManagement sections. They just need to be bound in the suites where needed and appropriate. The test poms under the suites should have this pom as their parent and set their relativePath appropriately The test poms under the suites inherit an empty 'child' profile from here. But any other build executions within the test poms should all be inside a 'child' profile.

How many classes does it take to make a cache? 60? 80? You might think so if you look at the other caches on the market. Ashkay is a streamlined, simple cache that in many ways is more powerful than the other mainstream caches. Ashkay is a strategy based caching tool. In most cases, you might be using a configuration file to tell the cache what rules it should obey. Or, you might just be setting properties on the cache. I have never liked this model as it limits me, the user of the cache to strategies the developer decided were important. Instead, Ashkay lets you choose the strategy(ies) to use when caching certain objects. Of course, a few of the most handy strategies are pre-packaged, but implementing a new one is a simple as can be. Ashkay is a fork of <a href="http://xot.sf.net">xot</a> caching code. Made more sense on its own.