Add comments about Filter and Functions.
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Wu Sheng
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## Documents
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[](README_ZH.md)
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* [SkyWalking Platform Overview](en/OAP/README.md)
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* Use application agents
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* Use service mesh probes
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* Deploy OAP backend
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We will begin to build our new documents for our new 6 version. Below it is 5.x document, wait for reformat.
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----------------------------
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* Getting Started
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* [Quick start](en/Quick-start.md)
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* [Install javaagent](en/Deploy-skywalking-agent.md)
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@ -11,7 +18,6 @@
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* [Trace Spring beans](en/agent-optional-plugins/Spring-bean-plugins.md)
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* [Trace Oracle and Resin](en/agent-optional-plugins/Oracle-Resin-plugins.md)
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* [[**Incubating**] Filter traces through custom services](../apm-sniffer/optional-plugins/trace-ignore-plugin/README.md)
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* [Architecture Design](en/Architecture.md)
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* Advanced Features
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* [Override settings through System.properties](en/Setting-override.md)
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* [Direct uplink and disable naming discovery](en/Direct-uplink.md)
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# Architecture Design
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## Background
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For APM, agent or SDKs are just the technical details about how to instrument the libs.
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Manual or auto are nothing about the architecture, so in this document, we will consider them as a client lib only.
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<img src="https://skywalkingtest.github.io/page-resources/5.0/architecture.png"/>
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## Basic Principles
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The basic design principles of SkyWalking architecture are **easy to maintain, controllable and streaming**.
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In order to achieve these goals, SkyWalking backend provides the following designs.
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1. Modulization design.
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1. Multiple connection ways for client side.
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1. Collector cluster discovery mechanism
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1. Streaming mode.
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1. Swtichable storage implementors.
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## Modulization
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SkyWalking collector is based on pure **modulization design**. End user can switch or assemble the collector features by their
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own requirements.
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### Module
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Module defines a collection of features, which could include techenical implementors(such as: gRPC/Jetty server managements),
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trace analysis(such as: trace segment or zipkin span parser), or aggregation feature. Totally decided by the module definition
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and its implementors.
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Each module could define their services in Java Interface,
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and every providers of the module must provide implementors for these services.
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And the provider should define the dependency modules based its own implementation.
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So it means, even two different implementors of the module, could depend different modules.
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Also the collector modulization core checks the startup sequences, if cycle dependency or dependency not found occurs,
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collector should be terminated by core.
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The collector startup all modules, which are decleared in `application.yml`.
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In this yaml file
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- Root level is the module name, such as `cluster`, `naming`
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- Secondary level is the implementor name of the module, such as `zookeeper` is the `cluster` module
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- Third level are attributes of the implementors. Such as `hostPort` and `sessionTimeout` are required attributes of `zookepper`.
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_The example part of the yaml definitation_
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```yml
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cluster:
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zookeeper:
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hostPort: localhost:2181
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sessionTimeout: 100000
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naming:
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jetty:
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#OS real network IP(binding required), for agent to find collector cluster
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host: localhost
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port: 10800
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contextPath: /
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```
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## Multiple connection ways
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First of all, the collector provides two types of connections, also two protocols(HTTP and gRPC). These two are
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1. Naming service in HTTP, which returns the all available collectors in the backend cluster.
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1. Uplink service in gRPC(primary in SkyWalking native agents) and HTTP, which uplinks traces and metrics to collector.
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Each client will only send monitoring data(traces and metrics) to a single collector. Attempt to connect other if the connected one offline.
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Such as in SkyWalking Java agent
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1. `collector.servers` means the naming service, which maps to `naming/jetty/ip:port` of collector, in HTTP.
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1. `collector.direct_servers` means setting Uplink service directly, and using gRPC to send monitoring data.
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_Example of the process flow between client lib and collector cluster_
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```
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Client lib Collector1 Collector2 Collector3
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(Set collector.servers=Collector2) (Collector 1,2,3 constitute the cluster)
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+-----------> naming service ---------------------------->|
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|<------- receive gRPC IP:Port(s) of Collector 1,2,3---<--|
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|Select a random gRPC service
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|For example collector 3
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|------------------------->Uplink gRPC service----------------------------------->|
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```
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## Collector Cluster Discovery
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When collectors are running in cluster mode, collector must discovery each other in some way. In default, SkyWalking uses
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Zookeeper to coordinate and as register center for instance discovery.
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Through the above section([Multiple connection ways](#multiple-connection-ways)), client lib will not use the Zookeeper to find cluster. And we suggest the client shouldn't do it in that way. Because the cluster discovery mechanism is switchable,
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provided by modulization core. Relying on that breaks the switchable capability.
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We hope the community provides more implementor to do cluster discovery, such as Eureka, Consul, Kubernate.
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## Streaming Mode
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Streaming mode likes a lightweight storm/spark implementation, which allows using APIs to build streaming process graph(DAG),
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and the input/output data contracts of each node.
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New module can find and extend the existed process graph.
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There are three cases in processing
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1. Synchronizing process. Tranditional method invocation.
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1. Asynchronizing process, a.k.a batch process based on Queue buffer.
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1. Remote process. Aggregate metrices across collector. In that way, selector is defined in node to decide
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how to find the collector in cluster. (HashCode, Rolling, ForeverFirst are the three ways supported)
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By having these features, collector cluster runs like as a streaming net, to aggregate the metrics and don't rely on the
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storage implementor to support writing the same metric id concurrently.
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## Swtichable Storage Implementors
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Because streaming mode takes care of the concurrent, storage implementor responsibilities are provide high speed write,
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and group query.
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Right now, we supported ElasticSearch as primary implementor, H2 for preview, and MySQL Relational Database cluster managed
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by ShardingShpere project.
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# Web UI
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Besides the principles in collector design, UI is another core component in SkyWalking. It is based on React, Antd and Zuul
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proxy to provide collector cluster discovery, query dispatch and visualziation.
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Web UI shares the similiar process flow as client's `1.naming then 2.uplink` mechanism in [Multiple connection ways](#multiple-connection-ways) section. The only difference is that, replace the uplink with GraphQL query protocol in HTTP binding at the host and port under `ui/jetty/` in yaml definition(default:`localhost:12800`).
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@ -170,20 +170,24 @@ including auto instrument agents(like Java, .NET), OpenCensus SkyWalking exporte
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| detectPoint | Represent where is the relation detected. Values: client, server, proxy. | yes | enum|
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#### Filter
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Use filter to build the conditions for the value of fields, by using field name and expression.
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Use filter to build the conditions for the value of fields, by using field name and expression.
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The expressions support to link by `and`, `or` and `(...)`.
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The OPs support `=`, `!=`, `>`, `<`, `in (v1, v2, ...`, `like "%..."`, with type detection based of field type. Trigger compile
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or code generation error if incompatible.
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#### Aggregation Function
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The default functions are provided by SkyWalking OAP core, and could implement more.
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The default functions are provided by SkyWalking OAP core, and could implement more.
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Provided functions
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- `avg`
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- `p99`
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- `p90`
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- `p75`
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- `p50`
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- `percent`
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- `histogram`
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- `sum`
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- `avg()`. The average value. The field type must be number.
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- `p99()`. The 99% of the given values should be greater or equal. The field type must be number.
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- `p90()`. The 90% of the given values should be greater or equal. The field type must be number.
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- `p75()`. The 75% of the given values should be greater or equal. The field type must be number.
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- `p50()`. The 75% of the given values should be greater or equal. The field type must be number.
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- `percent()`. The percentage of selected by filter in the whole given data. No type requirement.
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- `histogram(start, step)`. Group the given value by the given step, begin with the start value.
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- `sum()`. The sum number of selected by filter. No type requirement.
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#### Metric name
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The metric name for storage implementor, alarm and query modules. The type inference supported by core.
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