on the database server which doesn’t have the size limitations of a List in Apex. New Techniques to Enhance Data Deduplication using Content based-TTTD Chunking Algorithm Hala AbdulSalam Jasim, Assmaa A. Fahad Department of Computer Science, College of Science University of Baghdad Baghdad, Iraq Abstract—Due to the fast indiscriminate increase of digital data, data reduction has acquired increasing concentration and It doesn’t bother to gather up all the ACTUAL ids in the database like in QLPK. Trying to do this via an Apex query would fail after 2 minutes. Sometimes more than one technique will be possible but with some practice and insight it will be possible to determine which technique will work best for you. A technique called data deduplication can improve storage space utilization by reducing the duplicated data for a given set of files. In my examples I am making all 800 requests in parallel. And during the data deduplication process, a hashing function can be combined to generate a fingerprint for the data chunks. Hi, Well i don't have that much experience with WPF, but i don't see why WPF can't consume a WCF data service. To implement client-side processing. Maybe you’ve never heard this term, or you’ve heard it mentioned and wondered exactly how it works, where it came from and how to apply it to your e-Learning development. In this informative and engaging video, Salesforce Practice Lead at Robots and Pencils, Daniel Peter, offers actionable, practical tips on data chunking for massive organizations. Techniques of data discretization are used to divide the attributes of the continuous nature into data with intervals. In the base 10 decimal system, 1 character can have 10 different values. of the most effective approaches for data reduction is Data Deduplication technique in which the redundant data at the file or sub-file level is detected and identifies by using a hash algorithm. Probably the most common example of chunking occurs in phone numbers. Advantages of chunking technique are that it can be applied in virtually any communication protocol (HTTP, XML Web services, sockets, etc.) In order words, instead of reading all the data at once in the memory, we can divide into smaller parts or chunks. ... a simple line plot can do the task saving time and effort spent on trying to plot the data using advanced Big Data techniques. In the main portion of the talk Peter describes data chunking. These parallel query techniques make it possible to hit a “ConcurrentPerOrgApex Limit exceeded” exception. This technique may be used in various domains like intrusion, detection, fraud detection, etc. The queryLocator value that is returned is simply the Salesforce Id of the server side cursor that was created. What’s the story behind content chunking? Peter identifies the user pain points in both of these cases. Typically, this challenge falls into one of two primary areas: the first issue is returning a large number of records, specifically when Salesforce limits query results. But how do we get all the Ids in between, without querying the 40M records? Time for a head to head comparison of both of these to see which one is faster. Hence, techniques derived from the Cognitive Load Theory (CLT) are employed and one of these techniques is chunking, which is a natural processing, storing, maintenance, and retrieval mechanism where long strings of stimuli (e.g. In fact, data mining does not have its own methods of data analysis. A WHERE clause would likely cause the creation of the cursor to time out, unless it was really selective. In fact, we can even request these queries in parallel! But you get the idea. Data deduplication is widely used in storage systems to prevent duplicated data blocks. Peter gives Salesforce users the tools they require in order to choose a pathway for analysis.