large data

Neither of these approaches are appealing when you're dealing with large data sets or trying to build user-friendly Web applications.

Given large data sets, whether they are text or numeric, it is often useful to group together, or cluster, similar items automatically.

In large data warehouse query processing, multi-joining of fact tables is often involved.

Because of the decoupled nature of this approach, service requests to the target can be handled efficiently even for large data volumes.

Three-phase UPS systems are used in most large data centers for power conditioning and battery back-up in the event of mains power failure.

Large data sets are no longer esoteric concerns for a few big companies, but are becoming commonplace.

On a large data set, the statistics from 10% of the data (or even less) are often still very representative of the total population.

Linear RAID is suitable when large data exceeding the individual size of any disk or partition must be used.

One of the most noticeable differences of an in-memory database system is the absence of large data block structures.

data distribution and collection can be spread across many servers , and participant hosts transfer large data unobtrusively.

As the name suggests, this is a ready-made Zend Framework component that you can use to paginate large data sets.

Large data pools will use a lot of memory, which can slow down the loading and starting of a Rational Performance Tester test.

The operation began after an internet provider in Berlin tipped off authorities when he noticed very large data transfers.

As you use computers, as you're surfing the web, especially in large data centers, it generates a lot of heat.

This may significantly impact the execution time of the rule when executed on a large data set.

The algorithm can be a better solution to the insurance industry in data mining large data volume and high efficiency requirements.

First, we get better performance by avoiding large data transfer between the application in the application server and the database server.

The assertion that such large data revisions must be driven by a political agenda is a tall claim.

Large data sets are often the result of multiple data feeds.

Therefore, the data cleansing server needs to be able to scale in order to process large data volumes.

When working with large data sets, this analysis can negatively impact the performance of the control when automatic resizing occurs.

Amongst other areas, Shim has managed a number of large Data Warehouse projects and led Agile and Infrastructure deployment projects.

They are looking to Intelligent Light to help them address the need to manage this large data and efficiently extract meaningful results.

Some statisticians argue for a tougher standard of proof when researchers are fishing in large data sets.

The second accessor retrieves only the column containing large data, but it does not retrieve data from this column automatically.

However, in a production environment with large data sets, lazy loading always provides advantages.

In a cloud environment, the MapReduce structure increases the efficiency of throughput for large data sets.

Implications for interpretation of observed spectra for single sources and statistical analysis of large data samples are discussed.

Hadoop can be used in many applications beyond simply computing word counts of large data sets.

In many countries there are a few natural bottlenecks, whether it be large data centers or right-of-ways.

Its parallel processing engine scales helps it process faster growing, large data volumes in continuously shrinking batch windows.

They are part of a wider effort by HP to get more business from companies that operate large data centers.

Provides high performance queries supporting interactive analysis , even over large data volumes .

"It will be a joy (through 4G) connecting to services demanding large data volumes or fast data traffic, " says TeliaSonera in a statement.

The efficiency of the proposed approach is shown by the experimental results on very large data sets.

Large data sets with escalating complexity have pushed traditional data mining techniques to new levels of processing demand.

We conclude that cache- oblivious algorithms do outperform traditional RAM-model algorithms when working on large data sets.

These fields tend to manipulate large data sets to assist the user in visualizing, estimating, or actually solving non-trivial problems.

Your company, an ISP, has a very large data center with roughly 4000 systems all monitored by a Network Operations Center.

The idea is to save money by storing software on somebody else's servers in large data centers.

For very large data sets, a scalable recommendation algorithm must perform the most expensive calculations offline.

This allows for the creation of truly enterprise scalable applications with large data sets via Domino.

Initial vector-space creation times can be long, especially for large data sets.

In large data centers, it is recommended that you dedicate specific Exchange 2003 servers to handle only inbound and outbound SMTP traffic.

The decision tree technique is a very effective method for classifying large data sets.

Thus the application is responsible for the logic of chunking large data and then grouping it after receiving.

Data Mining, which extracts useful information from large data sets or databases, is a rising cross subject.

When it comes to developing large, data-centric applications, RIAs are generally strong .

This paper researches the stability of the anqing copper mine deep mining on the base of large data.

Such rules can be discovered efficiently from even very large data sets.

Image data is characterized by its special coding structure, large data volume and higher real-time demands.

To work around these issues, Srikanth Mandadi suggests splitting large data models into smaller subsets.

Large data graphics processing speed. 15M more instantaneous data can be disposed of.

We need large data sets that provide detailed environmental, demographic, and genetic data to find answers.

That large data set allowed them to analyze information for the 50 U. S. states separately, and also to identify trends by race and gender.

I think of large data-set visualization as a "Fly Through My Empire" application.

Finally, Pig is a platform for large data set analysis that includes a high-level language for Hadoop programming.

But in large data sets, on average, an asymmetry what you find.

The algorithm described here should scale to very large data sizes and very large machine sizes.

Large-scale index operations, performed offline or online, can generate large data loads that can cause the transaction log to quickly fill.

Accessor 0 is an automatic accessor; it retrieves all the columns except the one with large data.

Processing of data as batch or real-time, including handling large volumes of large data sets.

Navigating through large data sets efficiently.

Although in search engine we mainly process large data sets, in other applications we also need to process a large mount of small files.

However, in most case, it can meet production requirements without large data sets for a specific application.

This is the simplest synchronization method, but can involve unnecessarily large data sets being exchanged, which can limit performance.

To reduce the visual cluttering on large data, we propose a highly efficient clustering algorithm based on space-filling curves on the GPU.

These weather charts are currently transmitted as graphical files and have rather large data size.

As multi source images have very large data range, how to complete quickly point transformation is difficult in image processing system.

Similarly, the use of "predictive analytics" on the basis of large data sets may transform health care.

Data mining is the process of seeking interesting or valuable information in large data bases.

For large data imports, this can cause the transaction log to fill rapidly.

Accessor 1 is not an automatic accessor; it retrieves the column with large data.

Improved performance and the ability to handle large data volumes.

Multimedia has large data and demands wide bandwidth.

Finally, Pig is a platform on Hadoop for analyzing large data sets.

Large-scale index operations can generate large data loads that can cause the transaction log to fill quickly.

The preferred storage for large data is to use the varchar(max), nvarchar(max), and varbinary(max) data types.

However, the SSNN models required offline training with large data sets of input-output data.

These applications typically have a very large data set and display a high information density per screen.

If you are working with large data sets, consider using a dedicated buffer pool for the table space.

However, the most efficient way to upload large data is through the stream interfaces.

Some of these are simple code changes; others require new thinking about how to handle large data problems.

You can have other methods update or fetch the large data on demand.

This works great when you deal with large data files.

A new method is proposed for sample selection in large data set.

For very large data sets it quickly becomes impractical, or even impossible, to use JavaScript for tasks such as sorting by a column.

Handle very large data sets using virtual mode.

In this article, you learned how to create a customized solution to accelerate the performance for Dojo TreeGrid to load large data.

Reading large data sets into memory.

PINAT is very useful for large data PPI study with easiest handling among available softwares.

Can be used at library of large data storage.

Do you see or foresee an increasing need for working with large data sets?

The baseball data comes from a large data file.

Using the either the Clob or Blob method is not an efficient way to upload large data.

These kinds of large data sets are poised to become one of the most important resources the Internet creates.

For example a narrow data range may return less than 5% of your total data while a large data range may return almost 90% of data.

Don't log large data objects (CLOBs, DBCLOBs, and BLOBs) unless necessary.

B IH noise ECG database of 105 large data processing, testing rate was 9912 correct.

It can help you process large data sets faster (by balancing workloads where and when needed).

What's so hard about very large data?

Most algorithms of blind detection are based on second order or high order statistics, all of which need a large data block.

One area that is ripe for parallelization is sorting and searching in large data sets.

As we take over enterprise stand is more and more, we can build a large data files, as a case, the own development is very good.

Data source views let you define a subset of the data that populates a large data warehouse.

This can impose a requirement for high bandwidth to accommodate frequent and large data calls to the cloud server. Advantage: Desktop

On the identification of representative samples from large data sets, with application to synoptic climatology

A GA-Based Clustering Algorithm for Large Data Sets with Mixed Numerical and Categorical Values

A CSA-Based Clustering Algorithm for Large Data Sets with Mixed Numeric and Categorical Values

An Automatic Memory Management Algorithm for Large Data Structure

Dojo's approach to dealing with large data sets is simple, elegant, and boils down to two things

The Research Into the Architecture of Large Data Warehouse

Half Automatization of the Architecture of Large Data Warehouses

Parameter learning for Bayesian networks with large data set

Network performance is significantly improved because it isn't bogged down with the processing and transmission of several large data files;

Research on issues in developing large data warehouses

The Large Data Center's Backup strategy and Implementation

The Design and Application of Large Data Analysis Software

Increase Default Packet Size for Large Data Fields

Work with large data items in a recordset

Large Data Warehouse-based Data Mining: a Survey

disjoint clustering of large data sets;

A Fast Calculating Method for Large Data Mode Power

Mining of Rough Set Theory for Large Data Table

Mixed EM algorithm for large data sets

Application of Large Data Base

The Large Data Direct Classifying Method Based on Hyper Surface

LDB Large Data Base System

A Method of Dealing with Large Data Based on Data Buffering