presented by alan eldridge sales consultant tableau software australia

PRESENTED BY

Alan EldridgeSales ConsultantTableau Software Australia

What we will cover…

©2011 Tableau Software Inc. All rights reserved.

• Architecture

• Scalability & Availability

• Caching

Overview


Tableau DesktopSelf-service visual

data analysis

Informationconsumers

(Tableau Reader)connectlive

extract

Web & mobileusers

(Tableau Server interactors)

Presentation

Tableau ServerRapid fire business intelligence

Repository

Security

Management/Automation

Data Server

Cache

connectlive

extract

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Architecture


Terminology


• Process – an instance of a computer program that is being executed. It has its own set of resources (e.g. memory) that are not shared with other processes.

• Thread – a process may run multiple threads to perform instructions in parallel. Threads within a process share resources (e.g. memory).

• Server – a program running to serve the requests of other programs. The term is also used to refer to a physical computer dedicated to run one or more services.

Tableau Server

Tableau Server

Relational

OLAP

Files

Data

Tableau Server

Relational

OLAP

Files

Data

Tableau Desktop

Command LineTools

Browser/Mobile

Clients

Tableau Server

Relational

OLAP

Files

Data

Tableau Desktop

Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load BalancerReceives incoming client requests and directs them to the appropriate service for action

Acts as a load balancer, routing traffic round-robin to service instances

Returns HTML responses to client

Single-process; multi-threaded

Tableau Server

Relational

OLAP

Files

Data

Tableau Desktop

Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Processes logins, content searches, user/group/permission management, and other tasks not related to visualizing data

Works in conjunction with data stored in the Repository

Multi-server; multi-process; multi-threaded

Tableau Server

Relational

OLAP

Files

Data

Tableau Desktop

Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Active Directory

Stores Tableau Server metadata: users, group assignments, permissions, projects, etc.

Also stores flat files used as data sources

Responds to queries from other services when they need metadata

Has a SQL interface so external applications can connect (read-only)

If used, verifies authentication in conjunction with the App Server and Repository

Repository

Tableau Server

Relational

OLAP

Files

Data

Data Source D

rivers Tableau Desktop

Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Active Directory

VizQL Server

Provides same functionality as Tableau Desktop, processing requests related to data visualisation

Includes built-in caching (more on this later…)

Multi-server; multi-process; multi-threaded

Native drivers need to be installed for each data source (32-bit)

Repository

Tableau Server

Relational

OLAP

Files

Data

Data Source D


Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Active Directory

VizQL Server

Data ExtractHost

Repository

Invoked when a visualisation including a data extract is published

Stores and processes data extracts

Multi-threaded; 64-bit

Tableau Server

Relational

OLAP

Files

Data

Data Source D


Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Active Directory

VizQL Server

Data ExtractHost

Backgrounder

Controls tasks that ensure Tableau Server is running smoothly and efficiently

When the Data Extract Host is used, also handles scheduled data refreshes

Multi-server; multi-process

Repository

Tableau Server

Relational

OLAP

Files

Data

Data Source D


Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Active Directory

VizQL Server

Data ExtractHost

Backgrounder

Data ServerInvoked when a data source is published

via Tableau Desktop

Serves as proxy between requests for data and individual data sources

Enables centralized metadata management for data sources and an additional layer of access control

Allows centralized driver deployment

Allows multiple workbooks to us the same data extract

Multi-server; multi-process; multi-threaded; 32-bit

Repository

Tableau Server

Relational

OLAP

Files

Data

Data Source D


Command LineTools

Browser/Mobile

Clients

Gatew

ay/Load Balancer

AppServer

Repository

Active Directory

VizQL Server

Data ExtractHost

Backgrounder

Data Server

Server Monitoring

What you see running…


Scalability & Availability


Terminology


• Scalability – scalability is about supporting multiple simultaneous actions, not about making a single action faster.

• Availability – the ability of a solution to be resistant to component failures. Increasing the availability of a solution will increase the cost.

Terminology


• Scale Up – adding more resources (CPU, RAM, etc) to a single server.

• Scale Out – adding more resources (CPU, RAM, etc) by adding more servers in a “cluster”.

• Multi-Process – adding more throughput by running multiple instances of a process or service. These can be on a single server or can be distributed across multiple servers.

• Multi-Threaded – within a process, being able to perform multiple tasks simultaneously across multiple CPUs.

Terminology


• Single Point of Failure – within a solution, a component that if it fails will cause the solution to fail as a whole.

• Active/Active – when all instances of a multi-process service will process requests.

• Active/Passive – when only some instances of a multi-process service will process requests and the other instances are only activated in the event of a component failure.

Server Scalability


Service Multi-Process Multi-Threaded High Availability

VizQL Server Yes Yes Active/Active

Data Server Yes Yes Active/Active

Application Server Yes Yes Active/Active

Backgrounder Yes No Active/Active

Data Extract Host No Yes Active/Passive

Repository No No Active/Passive

Gateway No No Manual Failover

Server Scalability

Primary Node

Starting with a single server – everything is installed on one machine…

Server Scalability

Primary Node

Scale up - add more resources and run more service instances if required.

Server Scalability

Server Scalability

Primary Node Worker Node

Scale out – add a worker node running some or all of the services.

Server Scalability

Server Scalability


Scale out – add a worker node running some or all of the services.

Server Scalability


If the extract host or the repository fail…

Server Scalability


… the standby will take over as the active.

Server Scalability


When the failure is repaired, it starts up in standby mode.

Server Scalability


Worker Node

Worker nodes don’t need all the services – e.g. handling lots of extract refreshes…

Server Scalability

Primary Node Worker NodeWorker Node

Separate the gateway and now our architecture starts to have HA properties…

Server Scalability

ServerDown


We can survive a total server failure of any worker node.

Server Scalability


For full HA, we require a failover gateway server.

Server Scalability

ServerDown

Worker NodeWorker Node

In the event of a gateway failure…

Server Scalability

ServerDown

Primary Node

Worker NodeWorker Node

… we activate the failover gateway, but this is not automatic.

Caching


Terminology


• Performance – the speed with which a single process can be completed, assuming no contention for resources.

• Caching – a transparent store of values that have been calculated so that future requests for the same data can be serviced more quickly.

Image Tile Cache


• Dashboards are delivered to the client as a series of image “tiles” – these are assembled to show the complete dashboard.

• We can use this cache if:• Same dashboard (duh!)• No per-user security• Same dashboard size

• Handled by the gateway service, one per VizQL worker node

Image Tile Cache


• There is one single, simple step you can take to maximise the reuse of image tiles…

• Fixed size dashboards!

If We Miss the Image Tile Cache…


VizQL Server

GatewayDashboard

2. Model Cache

1. Tile Cache

Model Cache


• When re-rendering the dashboard we check to see if computations have already be done• calculated fields, table

calculations, reference lines, trend lines, etc

• We can use this cache if:• No change to data• No change to calcs

• Model cache is RAM based per VizQL server instance

If We Miss the Model Cache…


VizQL Server

GatewayDashboard

2. Model Cache

3. Query Result Cache

1. Tile Cache

Query Result Cache


• The query result cache holds the results from queries we have sent to data sources

• We can use this cache if:• Dimensions and measures

are the same• Filters are the same – this

means no per user security• Cache has not expired or is

not explicitly bypassed

• Query result cache is RAM based per VizQL server instance

Managing Caching


• Model cache• vizqlserver.modelcachesize:30• The number of models to cache, where there is one model per

viz instance in a workbook

• Query result cache• vizqlserver.querycachesize:64• The size in megabytes of query results to cache


Managing Caching


• Distributing components is a scalability strategy, not a performance strategy

• Caching is per-process• Distribution can hurt performance due to missing the cache

Managing Caching

One Last Layer…


VizQL Server

GatewayDashboard

Data Extract

2. Model Cache

3. Query Result Cache

1. Tile Cache

Extracts


• Also can be used as a form of cache to improve user response times• Using aggregated extracts

can improve performance even further (at the sacrifice of granularity)

• Can be scheduled to refresh fully or incrementally

• Using the Data Server they can be shared across multiple workbooks

Extracts


Summary


• Tableau Server provides a flexible, scalable architecture that (in general) can look after itself.

• Growing a Tableau Server installation to support more users and data is simple and does not require deep technical skills.

• By understanding how Tableau Server’s caching mechanisms work, we can design our dashboards for optimal performance.• Unless you have a reason not to, make all dashboards fixed

size.

Q&A


presented by alan eldridge sales consultant tableau software australia

Documents

tableau server slide

server monitoring slide

data visualisation

tableau desktop serves

individual data sources

visualizing data works

repository repository

live extract slide