unsupervised streaming

1. Introduction to Spark streaming 1.1 Overview Spark Streaming is an extension of the Spark core API that enables the processing of high-throughput, fault-tolerant real-time streaming data. Support for obtaining data from a variety of data sources, including KAFK, Flume, Twitter, ZeroMQ, Kinesis, and TCP sockets, after acquiring data from a data source, you can

Pick Want streaming media file format plays an important role in streaming media system, so designing a reasonable file format is the most direct and effective way to improve the efficiency of streaming media server. Based on the analysis of the common streaming media system and file format, this paper In particular,

First, Local: Using JAVACV (Android and Java Platform recommended JAVACV), FFmpeg, OpenCV or JMF can easily get to the local camera streaming media JAVACV Series articles: JAVACV Development 1: Call native webcam video JAVACV Development in Detail 2: The implementation of the converter, push the local camera video to the streaming media server and camera recording video func

The IIS live Smooth streaming (real-time smooth streaming) is Microsoft's next generation streaming media solution. The technology is to integrate the media transport platform IIS Media Services in the IIS Web to enable the use of standard HTTP Web technology and advanced Silverlight functionality to ensure the best quality and smooth audio and video broadcasts o

first of all, I admire eguid, whether it is technology or sharing, thanks to his series of Bowen on my first learning process help, so clearly indicated the reprint address: http://blog.csdn.net/eguid_1/article/details/51725970 one, the local push to send the end1, Local: The use of JAVACV (Android and Java Platform recommended JAVACV), FFmpeg, OpenCV or JMF can be very convenient access to the local camera streaming media JAVACV Series arti

From http://www.dataguru.cn/article-9532-1.html The demand for distributed streaming is increasing, including payment transactions, social networks, the Internet of Things (IoT), system monitoring, and more. There are several applicable frameworks for convection processing in the industry, so let's compare the similarities and differences of each stream processing framework.Distributed stream processing is the continuous processing, aggregation and a

Real-time streaming processing complete flow based on flume+kafka+spark-streaming 1, environment preparation, four test server Spark Cluster Three, SPARK1,SPARK2,SPARK3 Kafka cluster Three, SPARK1,SPARK2,SPARK3 Zookeeper cluster three, SPARK1,SPARK2,SPARK3 Log Receive server, SPARK1 Log collection server, Redis (this machine is used to do redis development, now used to do log collection test, the hostname

Contents of this issue:　　1. Spark Streaming Architecture2. Spark Streaming operating mechanism　　Key components of the spark Big Data analytics framework: Spark core, spark streaming flow calculation, Graphx graph calculation, mllib machine learning, Spark SQL, Tachyon file system, Sparkr compute engine, and more.　　　　Spark str