Download JAR files tagged by read with all dependencies

Extensions built on Microsoft Azure Event Hubs${line.separator} This library has been replaced by new Azure SDKs, you can read about them at https://aka.ms/azsdkvalueprop. The latest libraries to interact with the Azure Event Hubs service are:${line.separator} 1. https://search.maven.org/artifact/com.azure/azure-messaging-eventhubs${line.separator} 2. https://search.maven.org/artifact/com.azure/azure-messaging-eventhubs-checkpointstore-blob${line.separator} It is recommended that you move to the new package.

Please note, a newer package azure-messaging-eventhubs for Azure Event Hubs is available at https://search.maven.org/artifact/com.azure/azure-messaging-eventhubs as of February 2020. While this package will continue to receive critical bug fixes, we strongly encourage you to upgrade. Read the migration guide at https://aka.ms/azsdk/java/migrate/eh for more details.

Please note, a newer package azure-messaging-eventhubs for Azure Event Hubs is available at https://search.maven.org/artifact/com.azure/azure-messaging-eventhubs as of February 2020. While this package will continue to receive critical bug fixes, we strongly encourage you to upgrade. Read the migration guide at https://aka.ms/azsdk/java/migrate/eh for more details.

Parso is a lightweight Java library designed to read SAS7BDAT datasets. The Parso interfaces are analogous to libraries designed to read table-storing files, for example, CSVReader library. Despite its small size, the Parso library is the only full-featured open-source solution to process SAS7BDAT datasets, both uncompressed, CHAR-compressed and BIN-compressed. It is effective in processing clinical and statistical data often stored in SAS7BDAT format. Parso allows converting data into CSV format.

ORC is a self-describing type-aware columnar file format designed for Hadoop workloads. It is optimized for large streaming reads, but with integrated support for finding required rows quickly. Storing data in a columnar format lets the reader read, decompress, and process only the values that are required for the current query.

This filter can, based on HTTP headers in a HttpServletRequest, compress data written to the HttpServletResponse, or decompress data read from the request. When supported by the client browser, this can potentially greatly reduce the number of bytes written across the network from and to the client. As a Filter, this class can also be easily added to any J2EE 1.3+ web application.

This is Java bases client library for using snapcx address validation and correction webservice. You can subscribe to tracking webservice (REST based and JSON payload) at https://snapcx.io/pricing. Also read more about this webservice at https://snapcx.io/addressValidation. Before using this client, you can check your api key using API explorer, running at https://snapcx.io/addressValidationAPI

REdis Serialization Protocol (RESP) implemented in java. You can simply construct string commands to RESP commands, and interpret redis response. By import net.yesdata.RESP_intepreter.* you can play with RESP with happy. How to format command string to RESP style? String command = "INFO"; IInterpreter intepreter = new DefaultRespInterpreter(); String sentCommand = intepreter.FormatCommand(command); How to read and print RESP style response? IInterpreter intepreter = new DefaultRespInterpreter(); List<IRespNode> respNodes = intepreter.IntepretResponse(responseBody); for(IRespNode n : respNodes) { System.out.println(n.toRespFormatString()); }

TrueVFS is a virtual file system (VFS) for Java 7 which enables client applications to perform CRUD (Create, Read, Update, Delete) operations on archive files as if they were virtual directories, even with nested archive files in multithreaded environments. As a library, TrueVFS provides simple, uniform, transparent, thread-safe, read/write access to archive files as if they were virtual directories in a file system path. As a framework, TrueVFS provides the API to write file system drivers which plug-in to its federated file system space.

HBase is the &lt;a href="http://hadoop.apache.org"&rt;Hadoop</a&rt; database. Use it when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware.