wso2 product release webinar: wso2 data analytics server 3.0

WSO2 Data Analytics Server 3.0.0Product Release Webinar

Inosh GoonewardenaAssociate Technical Lead

WSO2 Analytics Platform

WSO2 Analytics Platform

Data Processing Pipeline

Introducing WSO2 Data Analytics Server

● Fully-open source solution with the ability to build systems and applications that collect and analyze data and communicate the results.

● Embodies the WSO2 Analytics Platform by combining batch, real-time, interactive and predictive analytics capabilities

● High performance data capture framework

● Highly available and scalable by design

Advantages of DAS 3.0 over WSO2 BAM 2.5.0

● Complete rewrite from the ground up, with performance and extensibility as core values

● Faster analytics powered by Apache Spark, 10x - 100x speedup

● Rich indexing support, with near real-time text search

● Pluggable data store support, from lightweight embedded RDBMS to highly scalable HBase/HDFS

● Revamped Analytics Dashboard with wizard-based gadget generation

WSO2 DAS Architecture

Collecting Data

Data Model{

'name': 'stream.name',

'version': '1.0.0',

'nickName': 'stream nickname',

'description': 'description of the stream',

'metaData':[

{'name':'meta_data_1','type':'STRING'},

],

'correlationData':[

{'name':'correlation_data_1','type':'STRING'}

],

'payloadData':[

{'name':'payload_data_1','type':'BOOL'},

{'name':'payload_data_2','type':'LONG'}

]

}

● Published data conforms to a strongly typed data stream

● One API for Batch and Real-time Analytics.

● Asynchronous and non-blocking nature enables extremely fast writes.

● Supports multiple transport adapters for data collection

Data Receiver

Highly Pluggable Event Receiver Architecture

Data Persistence● Data Abstraction Layer to enable pluggable data connectors

○ RDBMS, Cassandra and HBase/HDFS offered. Custom connectors could be easily written

● Analytics Table○ The data persistence entity in WSO2 Data Analytics Server

○ Provides a backend data source agnostic way of storing and retrieving data

○ Allows applications to be written in a way that it does not depend on a specific data source, e.

g. JDBC (RDBMS), Cassandra APIs etc.

○ WSO2 DAS gives a standard REST API in accessing the Analytics Tables

Data Persistence● Analytics Record Stores

○ An Analytics Record Store houses a specific set of Analytics Tables

○ The Analytics Record Stores to be used for storing incoming events and storing query

processing output are configurable

○ Single Analytics Table namespace, the target record store only given at the time of table

creation

○ Useful in creating Analytics Tables where data will be stored in multiple target databases

● Analytics File System○ The location where the indexing data is stored

○ Multiple implementations provided OOTB, or custom implementations can be written

Analyzing Data

Batch Analytics

Batch Analytics - Overview● Powered by Apache Spark for 10x-100x higher performance than Hadoop

● Parallel, distributed with optimized in-memory processing

● Scalable script-based analytics written using an easy-to-learn, SQL-like query language powered by Spark SQL

● Interactive built in web interface for ad-hoc query execution

● Scheduled query script execution support with high-availability and failover

● Run Spark on a single node, Spark embedded Carbon server cluster or connect to external Spark cluster

create temporary table product_data using CarbonAnalytics

options (schema …)

create temporary table products using CarbonAnalytics

options (schema …)

insert into products select product_name from product_data

group by …

Batch Analytics - Spark SQL

Batch Analytics - Interactive Console

Batch Analytics - Spark Scripts

Interactive Analytics

● Full text data indexing support powered by Apache Lucene● Drill down search support● Distributed data indexing

○ Designed to support scalability● Near real-time data indexing and retrieval

○ Data indexed immediately as received

Interactive Analytics

Interactive Analytics

Real-time Analytics

What is Real-time Analytics?Real-time Analytics in

→

Real-time Analytics in →

● Gather data from multiple sources● Correlate data streams over time● Find interesting occurrences ● And Notify ● All in real-time

What is Real-time Analytics?

Predictive Analytics (upcoming)

Predictive Analytics in →

What is Predictive Analytics?

Predictive Analytics in →

● Extract, pre-process, and explore data

● Create models, tune algorithms and make predictions

● Integrate for better intelligence

What is Predictive Analytics?

Communicating Results

Dashboards● “Overall idea” in a glance (e.g. car

dashboard)

● Support for personalization, you can build your own dashboard.

● The entry point for Drill-down

● Building a custom dashboard○ Dashboard via Google Gadgets and content

via HTML5 + JavaScript○ Leverages WSO2 User Engagement Server to

build a dashboard.○ Uses charting libraries like Vega, D3.js

Dashboards: Gadget Generation Wizard

● Start with data in tabular format

● Map each column to dimension in your plot like X,Y, color, point size, etc

● Also do drill downs

● Create a chart with few clicks

Alerts● Detecting conditions can be

done via CEP Queries

● “Last Mile” is key○ Email

○ SMS

○ Push notifications to a UI

○ Pager

○ Trigger physical Alarm

APIs● With mobile Apps, most data are

exposed and shared as APIs (REST/JSON ) to end users.

● Analytics results can be exposed through APIs

○ REST API

○ JavaScript API

What can WSO2 DAS do for you?

Common Use Cases of WSO2 DAS● KPI Statistics

○ Application Statistics Monitoring○ Network / Service Statistics○ Sensor Data Aggregation

● Solving Optimization Problems○ Urban Planning○ Revenue Distribution Analysis

● Activity Monitoring○ Tracking Message Flows

● HL7 Data Exploration○ ESB HL7 Transport Interfaced with

DAS

● Log Analysis○ Application / System Logs

● Sports○ Real-time Analysis of Player

Performance○ Real-time Match Analysis

● Geo-Spatial○ Traffic Monitoring and Alerting○ Geo-fencing

● Anomaly Detection○ Fraud Detection○ Network Intrusion Detection○ Server Health Monitoring

API Statistics

API Statistics

HTTP Monitoring

Activity MonitoringActivity monitoring is for tracking events from multiple nodes in a flow to understand a specific activity

● Example:○ A client initiating a web services request which travels through multiple ESBs, application

servers and returns back. This flow will be uniquely identified and visualized in DAS

● Used for tracing messages, finding performance hotspots in the flow

● Implemented based on a correlation id based mechanism using Interactive Analytics

Activity Monitoring

Activity Monitoring

Activity Monitoring

Activity Monitoring

Activity Monitoring

Fraud Detection

● Built for detecting credit card fraud

● The rules are extensible with customized Siddhi execution plans for any type of fraud detection

● Currently leverages Real-time and Interactive Analytics features

Source: multichannelmerchant.com

Log Analysis● Distributed indexing and searching

of any type of logs stored in the system

● Notifications support with Real-time event processing features

● Application / Server health prediction with Machine Learning

● Utilizes Interactive + Real-time Analytics + Machine Learning features

Source: www.retrospective.centeractive.com

Urban Route Planning

Urban Route Planning

Product Demonstration

Questions?