mirror of
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Remove GMS GraphQL Service (#3605)
This commit is contained in:
Arun Vasudevan
GitHub
parent
e6b4343adb
commit
fde42e01e2
@ -1,571 +0,0 @@
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# DataHub GMS GraphQL Service
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> **Disclaimer**: DataHub's standalone GraphQL Service is now deprecated. The GraphQL API is now served from the [Metadata Service](../metadata-service/README.md) directly.
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> To explore the GraphQL Query & Mutation types, visit `<your-datahub-url>/api/graphiql`.
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Datahub GMS GraphQL Service wraps the Generalized Metadata Store (GMS) Rest.li calls around a GraphQL API.
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## Pre-requisites
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* You need to have [JDK8](https://www.oracle.com/java/technologies/jdk8-downloads.html)
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installed on your machine to be able to build `Datahub GMS GraphQL Service`.
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## Build
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To build `Datahub GMS GraphQL Service`
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`
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./gradlew :datahub-gms-graphql-service:build
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`
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## Dependencies
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Before starting `Datahub GMS GraphQL Service`, you need to make sure that [DataHub GMS](../metadata-service/README.md) is up and running.
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## Start via Docker image
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Quickest way to try out `Datahub GMS Graphql Service` is running the [Docker image](../docker/datahub-gms-graphql-service).
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## Start via command line
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If you do modify things and want to try it out quickly without building the Docker image, you can also run
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the application directly from command line after a successful [build](#build):
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```
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./gradlew :datahub-gms-graphql-service:bootRun
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```
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## API Calls
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Inorder to Start using the graphql API we would recommend you download [GraphiQL](https://www.electronjs.org/apps/graphiql)
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`Endpoint`: http://localhost:8091/graphql
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## Sample API Calls
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### Query Dataset
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Request:
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```
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{
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dataset(urn: "urn:li:dataset:(urn:li:dataPlatform:foo,bar,PROD)") {
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urn
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platform
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name
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origin
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description
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platformNativeType
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uri
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tags
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ownership {
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owners {
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owner {
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username
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urn
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info {
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displayName
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email
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fullName
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manager {
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urn
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}
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}
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editableInfo {
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aboutMe
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skills
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}
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}
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type
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source {
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url
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}
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}
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lastModified {
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actor
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}
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}
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created {
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actor
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}
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lastModified {
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actor
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}
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}
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}
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```
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Sample Response:
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```
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{
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"data": {
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"dataset": {
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"urn": "urn:li:dataset:(urn:li:dataPlatform:foo,bar,PROD)",
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"platform": "urn:li:dataPlatform:foo",
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"name": "bar",
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"origin": "PROD",
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"description": "Sample Dataset",
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"platformNativeType": null,
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"uri": null,
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"tags": [
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"Datahub",
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"Sample"
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],
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"ownership": {
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"owners": [
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{
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"owner": {
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"username": "fbar",
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"urn": "urn:li:corpuser:fbar",
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"info": {
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"displayName": "Foo Bar",
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"email": "fbar@linkedin.com",
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"fullName": "Foo Bar",
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"manager": {
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"urn": "urn:li:corpuser:datahub"
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}
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},
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"editableInfo": {
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"aboutMe": "About Me",
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"skills": [
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"Java",
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"SQL"
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]
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}
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},
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"type": "DATAOWNER",
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"source": null
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}
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],
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"lastModified": {
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"actor": "urn:li:corpuser:fbar"
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}
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},
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"created": {
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"actor": "urn:li:corpuser:fbar"
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},
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"lastModified": {
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"actor": "urn:li:corpuser:fbar"
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}
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}
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}
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}
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```
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### Query MLModel
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Sample Request:
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```
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{
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mlModel(urn: "urn:li:mlModel:(urn:li:dataPlatform:science,scienceModel,PROD)") {
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urn
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type
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name
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origin
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description
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tags
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ownership {
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owners {
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owner {
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urn
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username
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editableInfo {
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pictureLink
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}
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info {
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firstName
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}
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}
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type
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source {
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type
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url
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}
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}
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}
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properties {
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description
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date
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version
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type
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hyperParameters {
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key
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value {
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...on StringBox {
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stringValue
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}
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... on IntBox {
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intValue
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}
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... on FloatBox {
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floatValue
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}
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... on BooleanBox {
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booleanValue
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}
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}
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}
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mlFeatures
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tags
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}
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status {
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removed
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}
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institutionalMemory {
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elements {
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url
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description
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created {
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actor
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}
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}
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}
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intendedUse {
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primaryUses
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primaryUsers
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outOfScopeUses
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}
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factorPrompts {
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relevantFactors {
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groups
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instrumentation
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environment
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}
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evaluationFactors {
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groups
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instrumentation
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environment
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}
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}
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metrics {
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decisionThreshold
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performanceMeasures
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}
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trainingData {
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dataset
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motivation
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preProcessing
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}
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evaluationData {
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dataset
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motivation
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preProcessing
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}
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quantitativeAnalyses {
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unitaryResults {
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...on StringBox {
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stringValue
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}
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}
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intersectionalResults {
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...on StringBox {
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stringValue
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}
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}
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}
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ethicalConsiderations {
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useCases
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humanLife
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mitigations
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risksAndHarms
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useCases
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data
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}
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caveatsAndRecommendations {
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caveats {
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caveatDescription
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needsFurtherTesting
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groupsNotRepresented
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}
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recommendations
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idealDatasetCharacteristics
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}
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cost {
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costType
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costValue {
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costId
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costCode
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}
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}
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}
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}
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```
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Sample Response:
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```
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{
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"data": {
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"mlModel": {
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"urn": "urn:li:mlModel:(urn:li:dataPlatform:science,scienceModel,PROD)",
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"type": "MLMODEL",
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"name": "scienceModel",
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"origin": "PROD",
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"description": "A sample model for predicting some outcome.",
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"tags": [
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"Sample"
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],
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"ownership": {
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"owners": [
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{
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"owner": {
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"urn": "urn:li:corpuser:jdoe",
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"username": "jdoe",
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"editableInfo": null,
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"info": {
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"firstName": null
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}
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},
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"type": "DATAOWNER",
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"source": null
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},
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{
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"owner": {
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"urn": "urn:li:corpuser:datahub",
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"username": "datahub",
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"editableInfo": {
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"pictureLink": "https://raw.githubusercontent.com/linkedin/datahub/master/datahub-web-react/src/images/default_avatar.png"
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},
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"info": {
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"firstName": null
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}
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},
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"type": "DATAOWNER",
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"source": null
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}
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]
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},
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"properties": {
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"description": "A sample model for predicting some outcome.",
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"date": null,
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"version": null,
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"type": "Naive Bayes classifier",
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"hyperParameters": null,
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"mlFeatures": null,
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"tags": [
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"Sample"
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]
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},
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"status": {
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"removed": false
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},
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"institutionalMemory": {
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"elements": [
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{
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"url": "https://www.linkedin.com",
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"description": "Sample doc",
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"created": {
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"actor": "urn:li:corpuser:jdoe"
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}
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}
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]
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},
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"intendedUse": {
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"primaryUses": [
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"Sample Model",
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"Primary Use"
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],
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"primaryUsers": [
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"ENTERPRISE"
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],
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"outOfScopeUses": [
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"Production Deployment"
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]
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},
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"factorPrompts": null,
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"metrics": {
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"decisionThreshold": [
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"decisionThreshold"
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],
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"performanceMeasures": [
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"performanceMeasures"
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]
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},
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"trainingData": [
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{
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"dataset": "urn:li:dataset:(urn:li:dataPlatform:hive,pageViewsHive,PROD)",
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"motivation": "For science!",
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"preProcessing": [
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"Aggregation"
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]
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}
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],
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"evaluationData": [
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{
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"dataset": "urn:li:dataset:(urn:li:dataPlatform:hive,pageViewsHive,PROD)",
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"motivation": null,
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"preProcessing": null
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}
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],
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"quantitativeAnalyses": null,
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"ethicalConsiderations": {
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"useCases": [
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"useCases"
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],
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"humanLife": [
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"humanLife"
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],
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"mitigations": [
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"mitigations"
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],
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"risksAndHarms": [
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"risksAndHarms"
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],
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"data": [
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"data"
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]
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},
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"caveatsAndRecommendations": {
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"caveats": null,
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"recommendations": "recommendations",
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"idealDatasetCharacteristics": [
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"idealDatasetCharacteristics"
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]
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},
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"cost": {
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"costType": "ORG_COST_TYPE",
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"costValue": {
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"costId": null,
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"costCode": "costCode"
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}
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}
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}
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}
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}
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```
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### Query DataFlow
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Request:
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```
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{
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dataFlow(urn: "urn:li:dataFlow:(airflow,flow1,foo)") {
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urn
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type
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orchestrator
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flowId
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info {
|
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name
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description
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project
|
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}
|
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ownership {
|
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owners {
|
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owner {
|
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username
|
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urn
|
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info {
|
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displayName
|
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email
|
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fullName
|
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manager {
|
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urn
|
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}
|
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}
|
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editableInfo {
|
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aboutMe
|
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skills
|
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}
|
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}
|
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type
|
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source {
|
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url
|
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}
|
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}
|
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lastModified {
|
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actor
|
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}
|
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}
|
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}
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}
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```
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Sample response:
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```
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{
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"data": {
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"dataFlow": {
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"urn": "urn:li:dataFlow:(airflow,flow1,foo)",
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"type": "DATA_FLOW",
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"orchestrator": "airflow",
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"flowId": "flow1",
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"info": {
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"name": "flow1",
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"description": "My own workflow",
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"project": "X"
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},
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"ownership": {
|
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"owners": [
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{
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"owner": {
|
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"username": "test-user",
|
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"urn": "urn:li:corpuser:test-user",
|
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"info": null,
|
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"editableInfo": null
|
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},
|
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"type": "DEVELOPER",
|
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"source": null
|
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}
|
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],
|
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"lastModified": {
|
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"actor": "urn:li:corpuser:datahub"
|
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}
|
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}
|
||||
}
|
||||
}
|
||||
}
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```
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|
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### Query DataJob
|
||||
|
||||
Request:
|
||||
|
||||
```
|
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{
|
||||
dataJob(urn: "urn:li:dataJob:(urn:li:dataFlow:(airflow,flow1,foo),task1)") {
|
||||
urn
|
||||
type
|
||||
jobId
|
||||
dataFlow {
|
||||
urn
|
||||
flowId
|
||||
}
|
||||
inputOutput {
|
||||
inputDatasets {
|
||||
urn
|
||||
name
|
||||
}
|
||||
outputDatasets {
|
||||
urn
|
||||
name
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Sample response
|
||||
|
||||
```
|
||||
{
|
||||
"data": {
|
||||
"dataJob": {
|
||||
"urn": "urn:li:dataJob:(urn:li:dataFlow:(airflow,flow1,foo),task1)",
|
||||
"type": "DATA_JOB",
|
||||
"jobId": "task1",
|
||||
"dataFlow": {
|
||||
"urn": "urn:li:dataFlow:(airflow,flow1,foo)",
|
||||
"flowId": "flow1"
|
||||
},
|
||||
"inputOutput": {
|
||||
"inputDatasets": [
|
||||
{
|
||||
"urn": "urn:li:dataset:(urn:li:dataPlatform:redis,stuff,PROD)",
|
||||
"name": "stuff"
|
||||
}
|
||||
],
|
||||
"outputDatasets": []
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
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@ -1,24 +0,0 @@
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plugins {
|
||||
id 'org.springframework.boot'
|
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id 'java'
|
||||
}
|
||||
|
||||
dependencies {
|
||||
compile project(':datahub-graphql-core')
|
||||
compile externalDependency.springBootStarterWeb
|
||||
compile 'com.graphql-java:graphql-java-spring-boot-starter-webmvc:2.0'
|
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compile 'com.graphql-java:graphiql-spring-boot-starter:5.0.2'
|
||||
compile externalDependency.graphqlJava
|
||||
compile externalDependency.antlr4Runtime
|
||||
compile externalDependency.antlr4
|
||||
compileOnly externalDependency.lombok
|
||||
annotationProcessor externalDependency.lombok
|
||||
}
|
||||
|
||||
configurations {
|
||||
compile.exclude group: 'org.neo4j', module: 'neo4j'
|
||||
}
|
||||
|
||||
bootJar {
|
||||
mainClassName = 'com.linkedin.datahub.graphql.service.GmsGraphQLApplication'
|
||||
}
|
||||
@ -1,20 +0,0 @@
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package com.linkedin.datahub.graphql.context;
|
||||
|
||||
import com.datahub.metadata.authorization.Authorizer;
|
||||
import org.springframework.stereotype.Component;
|
||||
import com.linkedin.datahub.graphql.QueryContext;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Data;
|
||||
|
||||
@Data
|
||||
@AllArgsConstructor
|
||||
@Component
|
||||
public class SpringQueryContext implements QueryContext {
|
||||
|
||||
boolean isAuthenticated;
|
||||
|
||||
String actor;
|
||||
|
||||
Authorizer authorizer;
|
||||
|
||||
}
|
||||
@ -1,25 +0,0 @@
|
||||
package com.linkedin.datahub.graphql.service;
|
||||
|
||||
import com.datahub.metadata.authorization.AuthorizationRequest;
|
||||
import com.datahub.metadata.authorization.AuthorizationResult;
|
||||
import com.datahub.metadata.authorization.Authorizer;
|
||||
|
||||
|
||||
/**
|
||||
* Implementation of {@link Authorizer} that allows all authorization requests. Used to keep backwards
|
||||
* compatibility with the deprecated DataHub Standalone GraphQL service.
|
||||
*/
|
||||
public class AllowAllAuthorizer implements Authorizer {
|
||||
|
||||
public AllowAllAuthorizer() { }
|
||||
|
||||
@Override
|
||||
public AuthorizationResult authorize(AuthorizationRequest request) {
|
||||
return new AuthorizationResult(null, null, AuthorizationResult.Type.ALLOW);
|
||||
}
|
||||
|
||||
@Override
|
||||
public AuthorizationMode mode() {
|
||||
return AuthorizationMode.ALLOW_ALL;
|
||||
}
|
||||
}
|
||||
@ -1,14 +0,0 @@
|
||||
package com.linkedin.datahub.graphql.service;
|
||||
|
||||
import org.springframework.boot.SpringApplication;
|
||||
import org.springframework.boot.autoconfigure.SpringBootApplication;
|
||||
import org.springframework.boot.autoconfigure.data.elasticsearch.ElasticsearchAutoConfiguration;
|
||||
import org.springframework.boot.autoconfigure.elasticsearch.rest.RestClientAutoConfiguration;
|
||||
|
||||
@SuppressWarnings("checkstyle:HideUtilityClassConstructor")
|
||||
@SpringBootApplication(exclude = {ElasticsearchAutoConfiguration.class, RestClientAutoConfiguration.class})
|
||||
public class GmsGraphQLApplication {
|
||||
public static void main(String[] args) {
|
||||
SpringApplication.run(GmsGraphQLApplication.class, args);
|
||||
}
|
||||
}
|
||||
@ -1,34 +0,0 @@
|
||||
package com.linkedin.datahub.graphql.service;
|
||||
|
||||
import javax.annotation.PostConstruct;
|
||||
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.stereotype.Component;
|
||||
|
||||
import com.linkedin.datahub.graphql.GmsGraphQLEngine;
|
||||
import com.linkedin.datahub.graphql.GraphQLEngine;
|
||||
|
||||
import graphql.GraphQL;
|
||||
|
||||
@Component
|
||||
public class GmsGraphQLProvider {
|
||||
|
||||
private GraphQL graphQL;
|
||||
private GraphQLEngine graphQLEngine;
|
||||
|
||||
@Bean
|
||||
public GraphQL graphQL() {
|
||||
return graphQL;
|
||||
}
|
||||
|
||||
@Bean
|
||||
public GraphQLEngine graphQLEngine() {
|
||||
return graphQLEngine;
|
||||
}
|
||||
|
||||
@PostConstruct
|
||||
public void init() {
|
||||
this.graphQLEngine = new GmsGraphQLEngine().builder().build();
|
||||
this.graphQL = graphQLEngine.getGraphQL();
|
||||
}
|
||||
}
|
||||
@ -1,35 +0,0 @@
|
||||
package com.linkedin.datahub.graphql.service;
|
||||
|
||||
import java.util.concurrent.CompletableFuture;
|
||||
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.context.annotation.Primary;
|
||||
import org.springframework.stereotype.Component;
|
||||
import org.springframework.web.context.request.WebRequest;
|
||||
|
||||
import com.linkedin.datahub.graphql.GraphQLEngine;
|
||||
import com.linkedin.datahub.graphql.QueryContext;
|
||||
import com.linkedin.datahub.graphql.context.SpringQueryContext;
|
||||
|
||||
import graphql.ExecutionResult;
|
||||
import graphql.spring.web.servlet.GraphQLInvocation;
|
||||
import graphql.spring.web.servlet.GraphQLInvocationData;
|
||||
|
||||
@Component
|
||||
@Primary
|
||||
public class QueryGraphQLInvocation implements GraphQLInvocation {
|
||||
|
||||
@Autowired
|
||||
GraphQLEngine graphQLEngine;
|
||||
|
||||
public static final String APPNAME = "GmsGraphQLApp";
|
||||
|
||||
@Override
|
||||
public CompletableFuture<ExecutionResult> invoke(GraphQLInvocationData invocationData, WebRequest webRequest) {
|
||||
QueryContext queryContext = new SpringQueryContext(true, APPNAME, new AllowAllAuthorizer());
|
||||
|
||||
return CompletableFuture.supplyAsync(() -> graphQLEngine.execute(invocationData.getQuery(),
|
||||
invocationData.getVariables(),
|
||||
queryContext));
|
||||
}
|
||||
}
|
||||
@ -1 +0,0 @@
|
||||
server.port=8091
|
||||
@ -1,37 +0,0 @@
|
||||
# Defining environment
|
||||
ARG APP_ENV=prod
|
||||
|
||||
FROM adoptopenjdk/openjdk8:alpine-jre as base
|
||||
ENV DOCKERIZE_VERSION v0.6.1
|
||||
RUN apk --no-cache add curl tar \
|
||||
&& curl -L https://github.com/jwilder/dockerize/releases/download/$DOCKERIZE_VERSION/dockerize-linux-amd64-$DOCKERIZE_VERSION.tar.gz | tar -C /usr/local/bin -xzv
|
||||
|
||||
# Workaround alpine issue with /lib64 not being in the ld library path
|
||||
# https://gitlab.alpinelinux.org/alpine/aports/-/issues/10140
|
||||
ENV LD_LIBRARY_PATH=/lib64
|
||||
|
||||
# Add glibc compat layer into alpine linux, needed by java-snappy if kafka topics are compressed with snappy
|
||||
RUN apk add libc6-compat
|
||||
|
||||
FROM openjdk:8 as prod-build
|
||||
COPY . datahub-src
|
||||
RUN cd datahub-src && ./gradlew :datahub-gms-graphql-service:build
|
||||
RUN cd datahub-src && cp datahub-gms-graphql-service/build/libs/datahub-gms-graphql-service.jar ../datahub-gms-graphql-service.jar
|
||||
|
||||
FROM base as prod-install
|
||||
COPY --from=prod-build /datahub-gms-graphql-service.jar /datahub/datahub-gms-graphql-service/bin/
|
||||
COPY --from=prod-build /datahub-src/docker/datahub-gms-graphql-service/start.sh /datahub/datahub-gms-graphql-service/scripts/
|
||||
RUN chmod +x /datahub/datahub-gms-graphql-service/scripts/start.sh
|
||||
|
||||
FROM base as dev-install
|
||||
# Dummy stage for development. Assumes code is built on your machine and mounted to this image.
|
||||
# See this excellent thread https://github.com/docker/cli/issues/1134
|
||||
|
||||
FROM ${APP_ENV}-install as final
|
||||
|
||||
RUN addgroup -S datahub && adduser -S datahub -G datahub
|
||||
USER datahub
|
||||
|
||||
EXPOSE 8091
|
||||
|
||||
CMD /datahub/datahub-gms-graphql-service/scripts/start.sh
|
||||
@ -1,17 +0,0 @@
|
||||
# Datahub GMS GraphQL Service Docker Image
|
||||
|
||||
## Run
|
||||
|
||||
To start `Datahub GMS GraphQL Service` along with all the dependencies
|
||||
|
||||
```
|
||||
docker-compose -p datahub -f docker-compose.yml -f docker-compose.override.yml -f docker-compose.dev.yml up datahub-gms-graphql-service
|
||||
```
|
||||
|
||||
To start `Datahub GMS GraphQL Service` only without any dependencies
|
||||
|
||||
```
|
||||
docker-compose -p datahub -f docker-compose.yml -f docker-compose.override.yml -f docker-compose.dev.yml up --no-deps datahub-gms-graphql-service
|
||||
```
|
||||
|
||||
For more details refer [Docker README](../README.md)
|
||||
@ -1,2 +0,0 @@
|
||||
DATAHUB_GMS_HOST=datahub-gms
|
||||
DATAHUB_GMS_PORT=8080
|
||||
@ -1,6 +0,0 @@
|
||||
#!/bin/sh
|
||||
|
||||
dockerize \
|
||||
-wait tcp://$DATAHUB_GMS_HOST:$DATAHUB_GMS_PORT \
|
||||
-timeout 240s \
|
||||
java -jar /datahub/datahub-gms-graphql-service/bin/datahub-gms-graphql-service.jar
|
||||
@ -1,14 +0,0 @@
|
||||
version: '3.8'
|
||||
services:
|
||||
datahub-gms-graphql-service:
|
||||
build:
|
||||
context: ../
|
||||
dockerfile: docker/datahub-gms-graphql-service/Dockerfile
|
||||
image: linkedin/datahub-gms-graphql-service:${DATAHUB_VERSION:-head}
|
||||
env_file: datahub-gms-graphql-service/env/docker.env
|
||||
hostname: datahub-gms-graphql-service
|
||||
container_name: datahub-gms-graphql-service
|
||||
ports:
|
||||
- "8091:8091"
|
||||
depends_on:
|
||||
- datahub-gms
|
||||
@ -196,7 +196,6 @@ module.exports = {
|
||||
"datahub-frontend/README",
|
||||
"datahub-graphql-core/README",
|
||||
"metadata-service/README",
|
||||
"datahub-gms-graphql-service/README",
|
||||
// "metadata-jobs/README",
|
||||
"metadata-jobs/mae-consumer-job/README",
|
||||
"metadata-jobs/mce-consumer-job/README",
|
||||
@ -227,7 +226,6 @@ module.exports = {
|
||||
"docs/deploy/confluent-cloud",
|
||||
// Purposely not including the following:
|
||||
// - "docker/datahub-frontend/README",
|
||||
// - "docker/datahub-gms-graphql-service/README",
|
||||
// - "docker/datahub-gms/README",
|
||||
// - "docker/datahub-mae-consumer/README",
|
||||
// - "docker/datahub-mce-consumer/README",
|
||||
|
||||
@ -4,7 +4,7 @@ The figure below shows the high-level system diagram for DataHub's Serving Tier.
|
||||
|
||||
|
||||
|
||||
The primary service is called [gms](../../metadata-service) and exposes a REST API for performing CRUD operations on metadata. The metadata service also exposes search and graph query API-s to support secondary-index style queries, full-text search queries as well as relationship queries like lineage. In addition, the [datahub-frontend](../../datahub-frontend) and [datahub-gms-graphql](../../datahub-gms-graphql-service) services expose a GraphQL API on top of the metadata graph.
|
||||
The primary service is called [gms](../../metadata-service) and exposes a REST API and a GraphQL API for performing CRUD operations on metadata. The metadata service also exposes search and graph query API-s to support secondary-index style queries, full-text search queries as well as relationship queries like lineage. In addition, the [datahub-frontend](../../datahub-frontend) service expose a GraphQL API on top of the metadata graph.
|
||||
|
||||
## DataHub Serving Tier Components
|
||||
|
||||
|
||||
@ -4,7 +4,7 @@
|
||||
|
||||
To deploy a new instance of DataHub, perform the following steps.
|
||||
|
||||
1. Install [docker](https://docs.docker.com/install/) and [docker-compose](https://docs.docker.com/compose/install/) (if
|
||||
1. Install [docker](https://docs.docker.com/install/), [jq](https://stedolan.github.io/jq/download/) and [docker-compose](https://docs.docker.com/compose/install/) (if
|
||||
using Linux). Make sure to allocate enough hardware resources for Docker engine. Tested & confirmed config: 2 CPUs,
|
||||
8GB RAM, 2GB Swap area, and 10GB disk space.
|
||||
|
||||
|
||||
@ -1,6 +1,5 @@
|
||||
include 'datahub-frontend'
|
||||
include 'datahub-graphql-core'
|
||||
include 'datahub-gms-graphql-service'
|
||||
include 'datahub-web-react'
|
||||
include 'metadata-service:auth'
|
||||
include 'metadata-service:restli-api'
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user