Apache storm Apache Apex与Apache Storm有何不同？
看起来很像Apache storm Apache Apex与Apache Storm有何不同？,apache-storm,stream-processing,apache-apex,bigdata,Apache Storm,Stream Processing,Apache Apex,Bigdata,看起来很像 用户在两个平台上都以有向无环图（DAG）的形式构建应用程序/拓扑。Apex使用操作员/溪流，Storm使用喷口/溪流/螺栓 它们都实时处理数据，而不是批处理 两者似乎都具有高吞吐量和低延迟 所以，乍一看，两者看起来都很相似，我不太明白其中的区别。有人能解释一下主要的区别吗？换句话说，我什么时候应该使用一个而不是另一个？体系结构存在根本性差异，这使得每个平台在延迟、扩展和状态管理方面都非常不同 在最基本的层面上, Apache Storm使用记录确认来保证消息传递 ApacheAp
- 用户在两个平台上都以有向无环图（DAG）的形式构建应用程序/拓扑。Apex使用操作员/溪流，Storm使用喷口/溪流/螺栓
- 它们都实时处理数据，而不是批处理
- 两者似乎都具有高吞吐量和低延迟
所以，乍一看，两者看起来都很相似，我不太明白其中的区别。有人能解释一下主要的区别吗？换句话说，我什么时候应该使用一个而不是另一个？体系结构存在根本性差异，这使得每个平台在延迟、扩展和状态管理方面都非常不同 在最基本的层面上,
体系结构和功能
+-------------------+---------------------------+---------------------+
| | Storm | Apex |
+-------------------+---------------------------+---------------------+
| Model | Native Streaming | Native Streaming |
| | Micro batch (Trident | |
+-------------------+---------------------------+---------------------+
| Language | Java. | Java (Scala) |
| | Ability to use non | |
| | JVM languages support | |
+-------------------+---------------------------+---------------------+
| API | Compositional | Compositional (DAG) |
| | Declarative (Trident) | Declarative |
| | Limited SQL | |
| | support (Trident) | |
+-------------------+---------------------------+---------------------+
| Locality | Data Locality | Advance Processing |
+-------------------+---------------------------+---------------------+
| Latency | Low | Very Low |
| | High (Trident) | |
+-------------------+---------------------------+---------------------+
| Throughput | Limited in Ack mode | Very high |
+-------------------+---------------------------+---------------------+
| Scalibility | Limited due to Ack | Horizontal |
+-------------------+---------------------------+---------------------+
| Partitioning | Standard | Advance |
| | Set parallelism at work, | Parallel pipes, |
| | executor and task level | unifiers |
+-------------------+---------------------------+---------------------+
| Connector Library | Limited (certification) | Rich library of |
| | | connectors in |
| | | Apex Malhar |
+-------------------+---------------------------+---------------------+
+------------+--------------------------+---------------------+
| | Storm | Apex |
+------------+--------------------------+---------------------+
| State | External store | Checkpointing |
| Management | Limited checkpointing | Local checkpointing |
| | Difficult to exploit | |
| | local state | |
+------------+--------------------------+---------------------+
| Recovery | Cumbersome API to | Incremental |
| | store and retrieve state | (buffer server) |
| | Require user code | |
+------------+--------------------------+---------------------+
| Processing | At least once | |
| Semantic | Exactly once require | At least once |
| | user code and affect | End to end |
| | latency | |
| | | exactly once |
+------------+--------------------------+---------------------+
| Back | Watermark on queue | Automatic |
| Pressure | size for spout and bolt | Buffer server |
| | Does not scale | memory and disk |
+------------+--------------------------+---------------------+
| Elasticity | Through CLI only | Yes w/ full user |
| | | control |
+------------+--------------------------+---------------------+
| Dynamic | No | Yes |
| topology | | |
+------------+--------------------------+---------------------+
| Security | Kerberos | Kerberos, RBAC, |
| | | LDAP |
+------------+--------------------------+---------------------+
| Multi | Mesos, RAS - memory, | YARN |
| Tenancy | CPU, YARN | full isolation |
+------------+--------------------------+---------------------+
| DevOps | REST API | REST API |
| Tools | Basic UI | DataTorrent RTS |
+------------+--------------------------+---------------------+
网络研讨会：ApacheApex（下一代Hadoop）vs.Storm-比较和迁移大纲添加ApacheFlink和ApacheBeam，所有DAG处理器也请添加用例，我更喜欢适合每种情况的用例。