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I noticed that Slack uses ID's of the form U023BECGF, and not the standard f3a7a018-02da-4cdb-944c-44d073536648 you often see
What is the reasoning for this?
The code you put in your question (U023BECGF) is not a valid or complete UUID. UUIDs are 16 bytes (octets) which are represented as 32 characters of hexadcimal as standard: RFC: https://www.ietf.org/rfc/rfc4122.txt
Under no encoding is U023BECGF a representation of a 16 bytes; it's too short.
It is plausable that these keys could be incorperated into a UUID but they are not one in themselvs.
The usual reason for smaller fields is storing less data.
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I want to store massive amounts of data, specifically the amount of text equivalent to a book. How can I go about this? Is there a type of data storage that makes this process faster/easier (aka is fit) for this type of operation?
There are limits, but not that much. A single database can have (with default configurations) over a billion tables and each table can be 32TB in size.
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I want to convert a string ordinal to a number in perl
I have searched but not get exact answer.
Example: if the input is
one it should be 1.
five hundred it should be 500.
three hundred it should be 300.
Is there any module to do this?
One of the best parts of Perl is CPAN and, sure enough, a couple minutes of poking around on metacpan turned up the Lingua::EN::Words2Nums module:
use Lingua::EN::Words2Nums;
$num=words2nums("two thousand and one");
$num=words2nums("twenty-second");
$num=words2nums("15 billion, 6 million, and ninteen");
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In Postgresql, the hstore and json datatypes seem to have very similar use cases. When would you choose to use one vs. the other? Initial thoughts:
You can nest with json; you can't with hstore
Functions for parsing json won't be available until 9.3
The json type is just a string. There are no built in functions to parse it. The only thing to be gained when using it is the validity checking.
Edit for those downvoting: This was written when 9.3 still didn't exist.It is correct for 9.2. Also the question was different. Check the edit history.
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What speed optimization techniques do antiviruses use today to scan a file, provided they have to check for all the signatures + the behavioral scan?
I'm not a antivirus programmer, but I think the scan engine scans through a file searching for known pattern inside. The greater number of patterns it can identify, the longer it will take to scan.
Optimization maybe similar to database optimization, with patterns indexing.
Identification Methods
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I want to select certain amount of data from one table. Based on those data, I want to check another two tables and insert into 2 tables.
So I want to iterate the resulted data. Which way is better(faster) and reasonable using DataReader or DataTable?
Thanks in advance
RedsDevils
You end up creating a reader to fill the table. The reverse isn't true, So I would stick with the dataReader.
-Josh