Apache Apex如何與Apache Storm不同？

Question

Apache Apex看起來像Apache Storm。

• 用戶在兩個平臺上構建應用程序/拓撲結構爲定向非循環圖（DAG）。 Apex使用操作員/流，Storm使用噴嘴/流/螺栓。
• 它們都是實時處理數據，而不是批處理。
• 似乎都具有高吞吐量&低延遲

所以，一目瞭然，看起來都差不多，我不太得到的差異。有人能解釋一下關鍵的區別嗎？換句話說，我應該什麼時候使用一個而不是另一個？

Answer 1

體系結構有着根本的不同，它使得每個平臺在延遲，縮放和狀態管理方面都有很大的不同。

在最基層，

1. 阿帕奇風暴使用記錄確認，以保證消息的傳送。
2. Apache Apex使用檢查點來保證消息傳遞。

您可以在以下博客中瞭解更多不同之處，其中還包括其他主流處理平臺。

https://databaseline.wordpress.com/2016/03/12/an-overview-of-apache-streaming-technologies/

Answer 2

架構和功能

+-------------------+---------------------------+---------------------+ 
|     |   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   | 
+-------------------+---------------------------+---------------------+ 

操作性

+------------+--------------------------+---------------------+ 
|   |   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  | 
+------------+--------------------------+---------------------+ 

來源： 研討會：阿帕奇頂點（下一代的Hadoop）與風暴 - 比較和遷移綱要https://www.youtube.com/watch?v=sPjyo2HfD_I