Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks for Open Source Streaming Analytics for Internet of Things Devices
Quarks, is available to the open source community that embeds streaming analytics onto Internet of Things (IoT) devices. Analyzing data at the edge continuously, can help companies generate insights
New Post has been published on http://www.predictiveanalyticstoday.com/quarks-for-open-source-streaming-analytics-for-internet-of-things-devices/?%SNAP%
This is another case of horrible horrible documentation from a large vendor.
IBM Streams is a streaming data processing platform. You write code (usually in their language) and the blocks are called operators. You create applications which are collections of operators. When you submit the applications to a Streams Instances they are called jobs. The jobs can split applications across multiple servers and it does this by splitting and running processing elements from your job on each server. The implication is your job/app is made up of processing elements which may or may not be collections of operators? So how do you define what is a processing element?
Unclear documentation also suggests that processing elements also ensure ordering/punctuation and that guarantees on ordering of streaming data is not guaranteed between processing elements unless you explicitly code to support that. I’ve not got to explore that yet so I can’t answer those questions here.
I can explain how you define a processing element. If you look through the development section of the manual you won’t find the answer. You can also search any of the streams books and likely not find it. You’ll find explanations of what PEs are though and how to administer them, but not how to control creation.
This seems like a basic thing that you would want to explain. I finally found it by searching on fusing operators. You’ll find the answer under the compilation and deployment section of their guide: http://www-01.ibm.com/support/knowledgecenter/SSCRJU_3.2.0/com.ibm.swg.im.infosphere.streams.spl-language-specification.doc/doc/compilationanddeployment.html
Basically when the manual talks about partitions that is equivalent to a Processing element. Every partition is one processing element. The compiler can be configured to automatically fuse operators (resulting in a PE) but by default each operator is it’s own PE. You can also specify a partition in your SPL code and operators inside that partition will become their own processing instance.
Simple enough... I just wish it hadn’t taken me 3 hours of searching/reading to find the answer.
If you want to control this explicitly, then the key to make your SPL application specify partitions (remember each partition is a PE) is the partitionColocation configuration in each operator. It specifies the name of which partition you would like your operator fused into.
Sample:
() as B2 = FileSink(B1) {
param file : "B.txt";
config placement : partitionColocation("B");
//fuse B2 into "B"
}
The documentation will also reference PECs. PEC is a processing element container. The scheduling of PEs is done by the PEC service within Streams so that the OS does not need to handle scheduling hundreds of processes within a highly parallel streaming application.
To sum it up.
Operator - A function
Partition - Defined in the SPL code but is a collection (fusion) of operators. A partition is the SPL equivalent of processing element.
Processing Element - A collection of 1->N operators (a partition).
Processing Element Container Service - Manages scheduling of processing elements within the IBM InfoSphere Streams environment.
