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Cloud-Native, Distributed Messaging and Streaming
幸运飞行艇 Apache Pulsar is an open-source, distributed messaging and streaming platform built for the cloud. Pulsar is proven at scale by hundreds of companies of different sizes, serving millions of messages per second.
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168飞艇公式计算最佳方法-幸运飞行艇官网app What is Pulsar
168飞艇 Apache Pulsar is an all-in-one messaging and streaming platform. Messages can be consumed and acknowledged individually or consumed as streams with less than 10ms of latency. Its layered architecture allows rapid scaling across hundreds of nodes, without data reshuffling.
Its features include multi-tenancy with resource separation and access control, geo-replication across regions, tiered storage and support for six official client languages. It supports up to one million unique topics and is designed to simplify your application architecture.
Pulsar is a Top 10 Apache Software Foundation project and has a vibrant and passionate community and user base spanning small companies and large enterprises.
168飞艇官网开奖记录查询-幸运飞行艇计划全天 Pulsar features
168飞艇4码计划稳定计划(非常准)-幸运飞行艇官方下载 Rapid Horizontal Scalability
Scales horizontally to handle the increased load. Its unique design and separate storage layer enable handling the sudden surge in traffic by scaling out in seconds.Low-latency messaging and streaming
Acknowledge messages individually (RabbitMQ style) or cumulative per partition (i.e., offset-like). Enables use cases such as distributed work queues or order-preserving data streams at very large scales (hundreds of nodes) and low latency (<10ms).Seamless Geo-Replication
Protect against complete zone outages using replication across different geographic regions. Flexible and configurable replication strategies across distant Pulsar Clusters. Uniquely supports automatic client failover to healthy clusters.Multi-tenancy as a first-class citizen
Maintain one cluster for your entire organization using tenants. Access control across data and actions using tenant policies. Isolate specific brokers to a tenant when maximum noisy neighbor protection is needed.Automatic Load Balancing
Add or remove nodes and let Pulsar load balance topic bundles automatically. Hot spotted topic bundles are automatically split and evenly distributed across the brokers.Official multi-language support
Officially maintained Pulsar Clients for Java, Go, Python, C++, Node.js, and C#.Official 3rd party integrations
Pulsar has officially maintained connectors with popular 3rd parties: MySQL, Elasticsearch, Cassandra, and more. Allows streaming data in (source) or out (sink).Serverless Functions
Write and deploy functions natively using Pulsar Functions. Process messages using Java, Go, or Python without deploying fully-fledged applications. Kubernetes runtime is bundled.Supports up to 1M topics
Pulsar's unique architecture supports up to 1 million topics in a single cluster. Simplify your own architecture by avoiding multiplexing multiple streams into a single topic.How does Pulsar work
Producer & Consumer
A Pulsar client contains a consumer and a producer. A producer writes messages on a topic. A consumer reads messages from a topic and acknowledges specific messages or all up to a specific message.
Apache Zookeeper
Pulsar and BookKeeper use Apache ZooKeeper to save metadata coordinated between nodes, such as a list of ledgers per topic, segments per ledger, and mapping of topic bundles to a broker. It’s a cluster of highly available and replicated servers (usually 3).
Pulsar Brokers
Topics (i.e., partitions) are divided among Pulsar brokers. A broker receives messages for a topic and appends them to the topic’s active virtual file (a.k.a ledger), hosted on the Bookkeeper cluster. Brokers read messages from the cache (mostly) or BookKeeper and dispatch them to the consumers. Brokers also receive message acknowledgments and persist them to the BookKeeper cluster as well. Brokers are stateless (don't use/need a disk).
Apache Bookkeeper
Apache BookKeeper is a cluster of nodes called bookies. Each virtual file (a.k.a ledger) is divided into consecutive segments, and each segment is kept on 3 bookies by default (replicated by the client - i.e., the broker). Operators can add bookies rapidly since no data reshuffling (moving) between them is required. They immediately share the incoming write load.
Pulsar use cases
A combination of unique and common use cases sets Pulsar apart from other message brokers.
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