Data processing method, client and distributed computing system
A technology of distributed computing and distributed system, applied in the field of client, distributed computing system, and data processing method, can solve the problems of prone to errors and many resources, so as to improve accuracy, reduce redis servers, and efficiently execute batches. effect of command
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Embodiment 1
[0057] see figure 1 , the present embodiment provides a distributed computing system 1, the distributed computing system includes 5 clients 11, 1 server 12, the server is a redis server, and the redis server includes several redis instances .
[0058] One of the five clients is a first client, and the first client includes an acquisition module 111, a processing module 112, a sending module 113, a setting module 114, a first judging module 115 and a second judging module Module 116.
[0059] The obtaining module is used to obtain data to be processed.
[0060] The first judging module is used for judging whether the data type of the key exists locally, if so, calling the processing module, otherwise calling the creating module.
[0061] The creation module is used to locally create the data type of the key value, and then call the processing module.
[0062] The processing module is used to process the data to be processed according to a preset rule to obtain a result valu...
Embodiment 2
[0085] see image 3 , this embodiment is basically the same as Embodiment 1, the only difference is:
[0086] Step 200 is executed after step 104 .
[0087] Step 200 , judging whether the time from the current moment to the last time to send data to be processed is greater than 5 seconds, if so, execute step 201 , otherwise return to step 100 .
[0088] Step 201. Send the data to be processed to obtain the result value to the redis server, and then execute step 204.
[0089] The data processing method, client, and distributed computing system of this embodiment can achieve the following effects: reduce the number of redis servers, because in the process of stream computing, the redis commands that will be generated locally will be simplified and compressed according to the data type, and will The commands that need to be processed centrally by the redis server are scattered on various stream computing machines, which can reduce the CPU, memory and other resources consumed by...
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