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Hitachi, Ltd.
Real-time management of real-world data
SOA platform CosminexusStream processing
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Time series processing can be easily created by using CQLTime
series processing can be easily created by using CQLTime series
processing can be easily created by using CQL
High-speed, time series processing of bulk dataHigh-speed, time
series processing of bulk data
Time series processing
Filtering Trend and pattern analyses Correlative analyses
Stream data processing infrastructureuCosminexus Stream Data
Platform
Aggregate and analytical scenariosReal world data
Log information
RFID data
Relational information ofpeople and objects
Creation of new values
Location-based services
Monitoring ofbusiness systems
Real-time distributionmanagement
Input Processing results
Due to the widespread use of broadband technologies and IC
cards, and the reduction of RFID costs, the quality and quantity of
real-world data that businesses handle have rapidly increased.In
order to meet this need, Cosminexus's stream data processing base,
uCosminexus Stream Data Platform, makes it possible to handle and
analyze large amounts of data in real time. uCosminexus Stream Data
Platform instantly ascertains system statuses and aids in the
decision-making process.
High-speed, time series processing of bulk dataTwo different
technologies are used to quickly process large amounts of data.
These technologies are called stream data processing and in-memory
data processing.Stream data processing is a technology that takes
large amounts of real-world data and time series processes it.
Instead of first saving the data into a database and then
processing it, this technology takes data as it occurs, extracts
any data according to a given scenario, and then analyzes only that
data.In-memory data processing is a technology that takes all the
data in use by an online system or a batch system, stores it in
memory, and then processes while in memory. This makes it possible
to process data faster than the alternative of retrieving the data
from hard drives in external storage. These technologies provides
better performance compared to conventional database processing
technologies.
Using a query language to easily created scenariosScenarios can
be created by using CQL, an extension of SQL. CQL is a very basic
language that is compatible with wide range of applications. Using
CQL with uCosminexus Stream Data Platform makes it possible to
perform the following types of time series processing:�
FilteringEssential data needed for analyses can be extracted.�
Trend analysesData trends can be analyzed from a given point in
time up to the present.� Correlation analysesVarious threads of
data can be analyzed, and correlations between the data can be
detected.What's more, there is no need to create a separate
application for scenarios. Scenarios can be easily added and
modified, as what is needed is just to apply scenarios by building
them in uCosminexus Stream Data Processing after simply defining in
text files.
Note
SQL: Structured Query Language
CQL: Continuous Query Language
Utilizing cutting-edge technology, large amounts of data can be
instantly analyzedUtilizing cutting-edge technology, large amounts
of data can be instantly analyzed
Real-time processing makes it possible to instantly analyze
large amounts of real-world data
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Stream data processing infrastructureuCosminexus Stream Data
Platform
Aggregate and analytical scenarios
IT system
Applicationserver
Web server
Databaseserver
Aggregate and analytical results
Memory usageCPU usage
Number of requests
Automatic analysis of the system-wide operational status
Prediction of surplus or insufficient resources
Stream data processing infrastructureuCosminexus Stream Data
Platform
Aggregate and analytical scenarios
Manufacturing management system Aggregate and analytical
results
Manufacturing management department
Production informationQuality information
Operation information
Manufacturing cost management
Early detection of equipment irregularities
Manufacturing site w
orkflow
Yield rate improvement
QA department
Maintenance department
Parts storage
Manufacturing line
Assembly line
Product warehouse
Monitoring of the whole system
Preventive monitoring
Early detectionof failures
Manufacturingcost trends
Whole-systemview
Early detectionof failures
Business site data
Manufacturing site data Defectiverate trends
uCosminexus Stream Data Platform can be used to analyze
real-world data in real time for a variety of industries, such as
the manufacturing, distribution, financial, and transportation
industries. The followings are just a few examples of the many
real-world uses of uCosminexus Stream Data Platform:- Using logs to
monitor business systems- Proactively or early detecting defects in
factory assembly lines- Automatically reading electric, gas, and
water meters, and billing the appropriate parties- Using RFID data
to manage distribution in real time- Using logs to check compliance
and to control network flows- Distributing information to people
and objects based on their position
Practical examplesSupporting stability in an IT
systemuCosminexus Stream Data Platform can take the massive amount
of log data generated from large, complicated IT systems, and then
time series process it to create an easy-to-view business system
overview. This makes it possible to monitor the operating status of
a business system in real time.Also, by analyzing trends and
correlations, possible system failures can be predicted and avoided
before they even occur. IT system stability can be supported
through these features of uCosminexus Stream Data Platform.
Supporting greater efficiency on manufacturing siteuCosminexus
Stream Data Platform can take manufacturing management system
sensor information and log information (i.e., production
information, quality information, and operation information), and
creates an easy-to-view map of the status of the manufacturing
floor.Also, defect trend analyses can be used to predict future
defects and improve the overall yield of a product line. A
high-level PDCA cycle can be supported through these features of
uCosminexus Stream Data Platform.
Handling real-world data in a variety of industriesHandling
real-world data in a variety of industries
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Hitachi, Ltd., Software Division5030
Totsuka-cho,Totsuka-ku,Yokohama-shi, Kanagawa-ken, 244-8555
JapanE-mail: [email protected]
Jul., 2010
Hitachi, Ltd.
Information service
http://www.hitachi.co.jp/soft-e/Information on Hitachi Open
Middleware is available at the following website:
http://www.hitachi.co.jp/soft-e/
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