confluent

function waits for a thread to terminate. Comparing threads to processes, pthread_creat is similar to fork, and Pthread_join is similar to Waitpid. We have to wait for the thread to TID, unfortunately, we have no way to wait for any thread to end. If the status pointer is not empty, the return value of the thread (a pointer to an object) is stored where the status points. A third function: pthread_t pthread_self(void); Threads have an ID to identify themselves within a given process. The thr

high for some real-time applications. Note that this issue are alleviated on a larger cluster. For example, suppose that there is partition leaders on a broker and there is ten other brokers in the same KAFKA CL Uster. Each of the remaining brokers only needs to fetch the partitions from the first broker on average. Therefore, the added latency due to committing a message would be just a few ms, instead of tens of Ms.As a rule of thumb, if you are about latency, it's probably a good idea-to-lim

Preface This is a study note.The learning material comes from a log blog post from Jay Kreps.The original text is very long, but I persisted to read, the harvest is very much, also deeply to Jay's technical ability, the architecture ability and to the distributed system understanding profound admiration. At the same time, because some understanding and Jay Brother's point of view coincide with slightly complacent. Jay Kreps is a former LinkedIn principal Staff Engineer, the current co-founder o

for better performance.KafkaAnnouncing the Confluent Platform 1.0 Kafka is described as the "central nervous system" of LinkedIn, which manages the flow of information gathered from various applications, which are processed and distributed throughout. Unlike the traditional enterprise information queuing system, KAFKA is processing all data flowing through a company in near real-time, and now has established a real-time information processing platfor

Transferred from: http://confluent.io/blog/stream-data-platform-2 http://www.infoq.com/cn/news/2015/03/apache-kafka-stream-data-advice/ In the first part of the live streaming data Platform Build Guide, Confluent co-founder Jay Kreps describes how to build a company-wide, real-time streaming data center. This was reported earlier by Infoq. This article is based on the second part of the collation. In this section, Jay gives specific recommendations fo

NEWMode retrieves existing patterns by subject, format, and versionby theme and formatRetrieves an existing schema by ID retrieves an existing schema byThemes, formats and versionsDelete Schema by IDDelete Schema Delete schema by topic31.5.2. Using the Confluent schema Registry31.6. Model Registration and Resolution31.6.1. Pattern registration Process (serialization)31.6.2. Pattern parsing process (deserialization)32. Inter-application communication3

idea to limit the number of partition per broker node: For Kafka clusters with B broker nodes and replication factor r, the partition number of the entire Kafka cluster is not better than 100* B*r, that is, the number of leader in a single partition is not more than 100. More partitions could Require morememory in the Client The more partition means that the client needs more memory In the most recent 0.8.2 release which we ship withthe confluent Pla

Preface This is a study note.The learning material comes from a log blog post from Jay Kreps.The original text is very long, but I persisted to read, the harvest is very much, also deeply to Jay's technical ability, the architecture ability and to the distributed system understanding profound admiration. At the same time, because some understanding and Jay Brother's point of view coincide with slightly complacent. Jay Kreps is a former LinkedIn principal Staff Engineer, the current co-founder o

Description This article is a translation of Kafka streams in the Confluent Platform 3.0 release. Original address: https://docs.confluent.io/3.0.0/streams/index.html Read a lot of other people to translate the document, or the first translation, there is no good translation of the place also please point out. This is the fourth article introduced by Kafka streams, the previous introduction is as follows: http://blog.csdn.net/ransom0512/article/detai

mentioned above Using confluent kafka-rest Proxy to implement the Kafka restful service (refer to the previous note), data transmission via HTTP protocol, it is necessary to pay attention to the use of Base64 encoding (or called encryption), If the message is not used before the Post base64 processing will appear: Server message garbled, program error, etc., so the normal process is:1. Deal with the message of post first UTF-8 unified processing2.

, Microsoft, confluent, Oracle, Hortonworks, Uber, and improve digital are contributing code for SAMZA. Samza has been widely used in business intelligence (BI), financial services, healthcare, security services, mobile applications, software development and other industries, including enterprise mobile application provider DoubleDutch, Europe's leading real-time advertising technology provider improve Digital, Financial services company Jack Henry A