"Note" This series of articles, as well as the use of the installation package/test data can be in the "big gift –spark Getting Started Combat series" get1 Spark Streaming Introduction1.1 OverviewSpark Streaming is an extension of the Spark core API that enables the processing of high-throughput, fault-tolerant real-ti
CustomReceiver(host, port))val words = lines.flatMap(_.split(" "))...
The full source code is in the example customer er. Scala.
The complete source code for this example is in customreceiver. Scala.
Implementing and using a custom actor-based Receiver
Custom akka actors can also be used to receive data.ActorHelperTrait can be applied on any akka actor, which allows stored ed data to be stored in Spark usingstore(...)Methods. The supervisor strategy of this actor can be configured to handle fa
for RTMP protocol playback. In addition the Flash Player is also a good choice to enter the address and stream name in the player:The playback effect is as follows, the computer desktop is truncated:To this, our entire crtmpserver source of the Windows platform of the compilation, Linux platform compilation, push stream, play even if complete. You can see that the compilation of Windows is more complex than Linux, in fact, a lot of open source software for Linux to be more friendly, including c
To realize the playback of media streaming files is very simple, as long as in the FMS server to provide good streaming media files, flash client through netconnection connected to the FMS server, and then through the NetStream loading on OK. about how to connect FMS in the first two of this series has been introduced in detail, first of all in FMS to establish a
What is Samza.
Apache Samza is a distributed streaming processing framework. It uses Apache Kafka for message sending and Apache Hadoop YARN to provide fault tolerance, processor isolation, security, and resource management. Dedicated to real-time data processing, much like Twitter's streaming system storm.
Recently, from the official Apache blog, the open source distributed
SOURCE Link: Spark streaming: The upstart of large-scale streaming data processingSummary: Spark Streaming is the upstart of large-scale streaming data processing, which decomposes streaming calculations into a series of short bat
Cloudera's enterprise data platform. In addition, Databricks is a company that provides technical support for spark, including the spark streaming.
While both can run in their own cluster framework, Storm can run on Mesos, while spark streaming can run on yarn and Mesos. 2. Operating principle 2.1 streaming architecture
Sparkstreaming is a high-throughput
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
NDK develops live streaming program for Android-side rtmp
After a toss-up, the success of the rtmp live streaming code, through the NDK cross-compiled way, ported to Android, thus realizing the Android side acquisition camera and mic seam data, then the H264 video encoding and AAC audio encoding, and sent to the RTMP server, To enable live Android camera. The program, called Ndkrtmpencoder, introdu
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 st
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
of Dstream is basically consistent with the RDD, which is based on the RDD and adds time dependence. The Rdd Dag can also be called a spatial dimension, meaning that the entire spark streaming a time dimension, or it can become a space and time dimension. From this perspective, spark streaming can be placed in a coordinate system. Where the y-axis is the operation of the Rdd, the dependency of the Rdd for
WSE3.0 Framework provides data optimization transport mechanism, WSE3.0 build Web Service Security (4): Mtom message transmission optimization and file upload, download questions are introduced. WCF also provides streaming operations to support the transfer and processing optimization of large data objects, and today we WCF distributed development Step-win series (4): Use flow operations (
media content, downloading the media resources, and reassembling the media content to the user in the form of continuous media streaming. In iOS 3.0 and later versions of the device, the client has been built into the QuickTime X and later versions of the desktop computer.
In a typical configuration, the hardware encoder accepts audio-video input, uses MPEG-4 encoding, outputs MPEG-2 TS streams, and then divides the segmented software into a
Live streaming weak network optimization strategy | live streaming SDK performance optimization practices, sdk Performance OptimizationScenarios of weak Network Optimization
After more than a year of rapid development, the online live broadcasting industry has developed a variety of methods. The earliest webcast was when the anchor sat in front of the PC and installed professional live video devices (such a
achieve HLS on demand, the focus is on the media file segmentation, there are many open source tools can be used, I will not discuss here, only talk about HLS live technology. A typical HTTP Live streaming streaming media system consists of content preparation, content distribution, and client software, as shown in the figure.
1. Content Preparation
The Content Preparation section is responsible for conver
Cloudera's enterprise data platform. In addition, Databricks is a company that provides technical support for spark, including the spark streaming.
While both can run in their own cluster framework, Storm can run on Mesos, while spark streaming can run on yarn and Mesos. 2. Operating principle 2.1 streaming architecture
Sparkstreaming is a high-throughput
, and spark streaming appears in MapR's distributed platform and Cloudera's enterprise data platform. In addition, Databricks is a company that provides technical support for spark, including the spark streaming.
While both can run in their own cluster framework, Storm can run on Mesos, while spark streaming can run on yarn and Mesos. 2. Operating principle
with those on-demand online video-on-demand websites, we are building the same server as they are, but the size is smaller ).Large Memory and hard disk capacity. The production and transmission of streaming media is the black hole of system resources, and large memory capacity is the prerequisite for stable system operation. streaming media files are large in size and require more storage space for a large
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