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(represented as an InputStream and OutputStream) They are converted into datagram packets for transmission over the network, without requiring the programmer to intervene (as shown in Figure 6-2) Figure 6-2 TCP deals with streams of data such as protocol commands, but converts streams into IP datagrams for transport over the network

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the query and the data in the domainAlthough it is not an actual measurement, it is still useful for comparison between different queries called against the same domain Given that query times tend to increase as domain size increases, keeping historical performance data can yield key insights when combined in a report along with historical domain metadata If you are able to log automated performance measurements, these reports can become trivially easy to produce

Airborne surveillance radars use space time adaptive processing (STAP) algorithms, which have been implemented as a parallel pipeline [CLW 00 + ] Each stage is itself a parallel algorithm, and the pipeline requires data redistribution between some of the stages

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Logging query performance measurements automatically is a powerful solution that delivers great insight with very little effortYou could do this yourself by adding a layer on top of any SimpleDB client, but it is best done as a built-in part of the client It is convenient when the client logs details of each request and response in a way very similar to the way a web server logs requests Web server logs have long been used to analyze data about web sites and about website usersAt a high level, web server logs are stored as text files with relevant information listed about each HTTP request, with one line per request It is an easy-to-parse format, and tools exist to read these log files using a user-specified configuration of fields and to generate reports Having a large set of historical data is useful for capacity planning and tracking performance metrics over time It also provides you with specific information for your own troubleshooting efforts and when dealing with AWS support Following is a list of useful fields you might want to log:

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several example applications [DGO 94 + ,SSOG93] that combine data parallelism (similar to the form of parallelism captured in the Geometric Decomposition pattern) and pipelining For example, one application performs 2D Fourier transforms on a sequence of images via a two stage pipeline (one stage for the row transforms and one stage for the column transforms), with each stage being itself parallelized using data parallelism The SIGPLAN paper ([SSOG93]) is especially interesting in that it presents performance figures comparing this approach with a straight data parallelism approach

The many advantages to using TCP over UDP are briefly summarized below 6111 Automatic Error Control Data transmission over TCP streams is more dependable than transmission of packets of information via UDP Under TCP, data packets sent through a virtual connection include a checksum to ensure that they have not been corrupted, just like UDP However, delivery of data is guaranteed by the TCP data packets lost in transit are retransmitted You may be wondering just how this is achieved after all, IP and UDP do not guarantee delivery; neither do they give any warning when datagram packets are dropped Whenever a collection of data is sent by TCP using data grams, a timer is started Recall our UDP examples from 5, in which the DatagramSocketsetSoTimeout method was used to start a timer for a receive() operation In TCP, if the recipient sends an acknowledgment, the timer is disabled But if an acknowledgment isn't received before the time runs out, the packet is retransmitted This means that any data written to a TCP socket will reach the other side without the need for further intervention by programmers (barring some catastrophe that causes an entire network to go down) All of the code for error control is handled by TCP 6112 Reliability Since the data sent between two machines participating in a TCP connection is transmitted by IP datagrams, the datagram packets will frequently arrive out of order This would throw for a loop any program reading information from a TCP socket, as the order of the byte stream would be disrupted and frequently unreliable Fortunately, issues such as ordering are handled by TCP each datagram packet contains a sequence number that is used to order data Later packets arriving before earlier packets will be held in a queue until an ordered sequence of data is available The data will then be passed to the application through the interface of the socket 6113 Ease of Use.

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