Tableau connector

This document provides setup documentation for the Tableau Connector (TabGo).

For a user guide, read aboutTableau dashboards.

TheTableau Analytics Extension APImakes it possible to integrateRapidMiner Gomodels and RapidMinerweb servicesinto Tableau dashboards. The same API is used by Tableau’s ownTabPyfor Python integration.

In what follows, RapidMiner's implementation of the API will be called TabGo. TabGo is an optional module for RapidMiner AI Hub, acting as a translation layer between Tableau and RapidMiner. By itself, TabGo does not execute prediction logic or run any analyses.

The setup documentation provided below consists of two parts:

Note that by default, TabGo isnot included in the docker-compose templatefor RapidMiner AI Hub. If TabGo is already installed (andtested!), you canskip ahead to step 2.

Install the connector on RapidMiner AI Hub

The following instructions assume that you are using adocker-compose基础安装RapidMiner AI中心。的进行guration differs slightly depending on whether RapidMiner AI Hub is configured to useHTTPSorHTTP.

However, the environment variables are always the same. In both scenarios you will have to add the following block to your.envfile:

# ############################################ # # TabGo # # ############################################ # Used for both TabGo and the TabGo proxy. TABGO_VERSION=9.9 # Proxy specific settings. TABGO_PROXY_PORT=4443 TABGO_BACKEND=http://rm-tabgo-svc # Settings for the TabGo service. TABGO_MAX_MEMORY=384m TABGO_PORT=8090 # Rate limit for small requests (e.g., scoring a single data row). The default # values limit the rate to 10 requests per 5 seconds. TABGO_SMALL_REQUEST_LIMIT=10 TABGO_SMALL_REQUEST_INTERVAL=5 # Change the log level to DEBUG to log HTTP traffic routed through TabGo. TABGO_LOG_LEVEL=INFO # Additional Java options should only be used for debugging. TABGO_JAVA_OPTIONS=

There are two settings that you might want to adjust:

If you expect TabGo to process large data sets, e.g., tables with tens of thousands of rows, or you expect many users in parallel, you should consider increasingTABGO_MAX_MEMORY.
If you expect many TabGo users in parallel, you may consider increasing theTABGO_SMALL_REQUEST_LIMITvariable. However, this limit exists for a good reason: without the limit, misconfigured dashboards may send hundreds of small requests, slowing Tableau to the point where the software becomes unresponsive. The offending behavior is usually caused by table calculations being computed line by line instead of in a single batch. For more details, see theCompute Usingoption fortable calculations.

Please note thatTABGO_LOG_LEVELis only meant to be changed temporarily for troubleshooting. Changing it toDEBUGwill impact TabGo’s performance and might leak sensitive information.

HTTPS configuration

If RapidMiner AI Hub is configured to use HTTPS, TabGo can pick up the existing configuration to secure the communication with Tableau. Adding the following two services to yourdocker-compose.ymlfile will configure TabGo to use the same certificate as the other RapidMiner AI Hub components:

rm-tabgo-svc: image: ${REGISTRY}rapidminer-tabgo:${TABGO_VERSION} restart: always hostname: rm-tabgo-svc environment: - TABGO_MAX_MEMORY=${TABGO_MAX_MEMORY} - TABGO_RMS_HOSTNAME=${RAPIDMINER_SERVER_URL} - TABGO_GO_HOSTNAME=${PUBLIC_URL} - TABGO_SMALL_REQUEST_LIMIT=${TABGO_SMALL_REQUEST_LIMIT} - TABGO_SMALL_REQUEST_INTERVAL=${TABGO_SMALL_REQUEST_INTERVAL} - TABGO_LOG_LEVEL=${TABGO_LOG_LEVEL} - _JAVA_OPTIONS=${TABGO_JAVA_OPTIONS} networks: rm-platform-int-net: aliases: - rm-tabgo-svc

rm-tabgo-proxy-svc: image: ${REGISTRY}rapidminer-tabgo-proxy:${TABGO_VERSION} hostname: rm-tabgo-proxy-svc restart: always environment: - HTTPS_CRT_PATH=${HTTPS_CRT_PATH} - HTTPS_KEY_PATH=${HTTPS_KEY_PATH} - TABGO_BACKEND=${TABGO_BACKEND} - TABGO_PORT=${TABGO_PORT} ports: - ${TABGO_PROXY_PORT}:443 depends_on: - rm-proxy-svc volumes: - ./ssl:/etc/nginx/ssl networks: rm-platform-int-net: aliases: - rm-tabgo-proxy-svc

After starting the new services, TabGo will listen on theTABGO_PROXY_PORTspecified in the.envfile.

HTTP configuration

If your RapidMiner AI Hub is configured to use HTTP, adding the following service to yourdocker-compose.ymlfile will enable TabGo:

rm-tabgo-svc: image: ${REGISTRY}rapidminer-tabgo:${TABGO_VERSION} restart: always hostname: rm-tabgo-svc ports: ${TABGO_PORT}:${TABGO_PORT} environment: - TABGO_MAX_MEMORY=${TABGO_MAX_MEMORY} - TABGO_RMS_HOSTNAME=${RAPIDMINER_SERVER_URL} - TABGO_GO_HOSTNAME=${PUBLIC_URL} - TABGO_SMALL_REQUEST_LIMIT=${TABGO_SMALL_REQUEST_LIMIT} - TABGO_SMALL_REQUEST_INTERVAL=${TABGO_SMALL_REQUEST_INTERVAL} - TABGO_LOG_LEVEL=${TABGO_LOG_LEVEL} - _JAVA_OPTIONS=${TABGO_JAVA_OPTIONS} networks: rm-platform-int-net: aliases: - rm-tabgo-svc

After starting the new service, TabGo will listen on theTABGO_PORTspecified in the.envfile.

Test the deployment

TabGo provides a simple/infoendpoint that you can call from any web browser. If the location of your RapidMiner AI Hub deployment is as indicated in the first column of the table below, the/infoendpoint will be as indicated in the second column.

	RapidMiner AI Hub	`/info`endpoint
HTTPS	https://aihub.company.test/	https://aihub.company.test:4443/info
HTTP	http://aihub.company.test/	http://aihub.company.test:8090/info

In both cases the endpoint should answer with a message in the following format:

{ "name": "TabGo", "description": "Tableau analytics connector to RapidMiner Go", "creation_time": 1602592657, "server_version": "9.9.0", "versions": { "v1": { "features": {} } } }

将表连接到RapidMiner AI中心

TabGo can be used together withTableau DesktopandTableau Server. All you need to provide is the endpoint on which TabGo is reachable.

Tableau Desktop

Within Tableau Desktop, configure anAnalytics Extension Connectionto TabGo underHelp > Settings and Performance > Manage Analytics Extension Connection…

Server- use the hostname for RapidMiner AI Hub
Port- use theportprovided by TabGo (by default 4443 for HTTPS / 8090 for HTTP)
Require SSL- check this box if you are using HTTPS

ClickTest Connectionto verify that Tableau Desktop is connected to TabGo:

Tableau Server

On Tableau Server, log in as administrator for the site where you want to enable the analytics connection.

Open the settings and navigate to theExtensionstab.
UnderAnalytics Extensions, checkEnable analytics extension for site.
As described above forTableau Desktop, enter the connection details for RapidMiner AI Hub.

Unfortunately, you cannot test the connection from within the Tableau Server settings. You will have to create a Tableau dashboard using TabGo to verify your configuration.

Once you have created theAnalytics Extension Connection, it is listed in settings as follows:

Categories

Versions