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For many applications, particularly applications where each of the data items is owned by exactly one user, consistency becomes a more narrow concern For example, consider an application that maintains a set of to-do lists for users If all of the lists are private, consistency involves how each user sees his or her own data, and it makes no difference to Jill whether Jack s data is consistent This narrowing holds even in cases where the data is made public Pretend that these are now wish lists and not to-do lists If Jack adds a new pail to his wish list, it is important that the publicly visible list be updated, but if that update is delayed by a full second, the delay is probably not even noticeable However, it is quite important for Jack to see a consistent view of his own list If he adds an item and then finds it immediately absent from the list, it will look like the update failedThis level of consistency, where each read reflects the results of every prior write by the same client, is called read-your-writes Allowing a client to see an always-consistent view of the data he is changing is a level of consistency that is useful in many situationsA relational database will give you this level of consistency automatically by virtue of the strong consistency guaranteeA relational database cluster, on the other hand, may not be able to guarantee read-your-writes when a slave database services client reads SimpleDB does not have the notion of a connected client, however, and does not guarantee read-your-writes consistency Each request is independent, and there is neither a persistent connection nor a session layerThis is not really a concern for batch-processing situations like indexing or data import; this is the concern when handling requests for connected users who are submitting updatesThis applies equally to application users for a website, a desktop app, or a mobile app It is important to realize that it is easy to build a system with guaranteed read-yourwrites consistency (or stronger) on top of SimpleDB by using consistent reads but that it comes by giving back some of the availability Having said that, it is possible to build a system that provides read-your-writes most of the timeThere is a situation that you need to be aware of when using SimpleDB during an outage, you may be unable to achieve read-your-writes for some users until the problem is resolved Knowing that, the remaining issue is the implementation of a system that can give you that consistency most of the time while still offering (potentially degraded) service during an outage.

#include <stdioh> #include <mathh> int main () { int i; int num_steps = 1000000; double x, pi, step, sum = 00; step = 10/(double) num_steps; for (i=0;i< num_steps; i++) { x = (i+05)*step; sum = sum + 40/(10+x*x); } pi = step * sum; printf("pi %lf\n",pi); return 0; }

will cause the server socket to accept requests on all local addresses If the port is already bound or security restrictions prevent access, an exception is thrown

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A program to carry this calculation out on a single processor is shown in Fig 52 To keep the program as simple as possible, we fix the number of steps to use in the integration at 1,000,000 The variable sum is initialized to 0 and the step size is computed as the range in x (equal to 10 in this case) divided by the number of steps The area of each rectangle is the width (the step size) times the height (the value of the integrand at the center of the interval) Because the width is a constant, we pull it out of the summation and multiply the sum of the rectangle heights by the step size, step, to get our estimate of the definite integral We will look at several versions of the parallel algorithm We can see all the elements of a classic SPMD program in the simple MPI version of this program, as shown in Fig 53 The same program is run on each UE Near the beginning of the program, the MPI environment is initialized and the ID for

When it comes down to the practical matter of how to deliver a consistent view to your users when consistent reads are failing, there are two types of strategy you can use: data access patterns and cachingThese techniques are independent and can be used together to achieve the best outcome Optimizing Data Access Patterns Many of the data access needs of an application are dictated by the application s requirements However, the database access patterns are frequently a consequence of application design Modern technologies, particularly web technologies, make it possible to sculpt

While the Socket class is fairly versatile, and has many methods, the Server Socket class doesn't really do that much, other than accept connections and act as a factory for Socket objects that model the connection between client and server The most important method is the accept() method, which accepts client connection requests, but there are several others that developers may find useful Methods All methods are public unless otherwise noted

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Socket accept() throws javaioIOException, javalangSecurity Exception waits for a client to request a connection to the server socket, and accepts

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