Answer:
A primary key is a special relational database table column (or combination of columns) designated to uniquely identify each table record. A primary key is used as a unique identifier to quickly parse data within the table. A table cannot have more than one primary key.
Primary Key.
Candidate Key.
Alternate Key.
Super Key.
Composite Key.
Foreign Key.
Unique Key.
In the relational model of databases, a primary key is a specific choice of a minimal set of attributes that uniquely specify a tuple in a relation. Informally, a primary key is "which attributes identify a record," and in simple cases constitute a single attribute: a unique ID.
Explanation:
Answer:
<u>the first friend</u>
Explanation:
It is important to <em>remember </em>that a core is the brain of the CPU (central processing unit), which means one who has a dual-core is having <em>"a dual brain" </em><em>to process information faster.</em>
Consider also, IT experts often acknowledge that in terms of speed of execution, it is proven that, "dual-core systems" are <em>faster</em> (even twice faster) than a "single-core system". The other friends were wrong because they disagreed with a widely accepted fact that dual-core is faster than single-core; and of course, <em>we know that without them being faster they can't run twice the applications and twice the data. </em>
Therefore, we can make the conclusion that the first friend's response is correct.
Answer:
For the first question I think it is chains
The second question.
The woman is suspicious at hotel doors have numbers so how could he have been confused
Explanation:
Answer:
It we were asked to develop a new data compression tool, it is recommended to use Huffman coding since it is easy to implement and it is widely used.
Explanation:
The pros and the cons of Huffman coding
Huffman coding is one of the most simple compressing encoding schemes and can be implemented easily and efficiently. It also has the advantage of not being patented like other methods (e.g. arithmetic codingfor example) which however are superior to Huffman coding in terms of resulting code length.
One thing not mentioned so far shall not be kept secret however: to decode our 96 bit of “brief wit” the potential receiver of the bit sequence does need the codes for all letters! In fact he doesn’t even know which letters are encoded at all! Adding this information, which is also called the “Huffman table” might use up more space than the original uncompressed sentence!
However: for longer texts the savings outweigh the added Huffman table length. One can also agree on a Huffman table to use that isn’t optimized for the exact text to be transmitted but is good in general. In the English language for example the letters “e” and “t” occur most often while “q” and “z” make up the least part of an average text and one can agree on one Huffman table to use that on average produces a good (=short) result. Once agreed upon it doesn’t have to be transmitted with every encoded text again.
One last thing to remember is that Huffman coding is not restricted to letters and text: it can be used for just any symbols, numbers or “abstract things” that can be assigned a bit sequence to. As such Huffman coding plays an important role in other compression algorithms like JPG compression for photos and MP3 for audio files.
The pros and the cons of Lempel-Ziv-Welch
The size of files usually increases to a great extent when it includes lots of repetitive data or monochrome images. LZW compression is the best technique for reducing the size of files containing more repetitive data. LZW compression is fast and simple to apply. Since this is a lossless compression technique, none of the contents in the file are lost during or after compression. The decompression algorithm always follows the compression algorithm. LZW algorithm is efficient because it does not need to pass the string table to the decompression code. The table can be recreated as it was during compression, using the input stream as data. This avoids insertion of large string translation table with the compression data.
