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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 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 understand that .collect(pf), where pf is a partial function, is the equivalent to .filter(pf.isDefinedAt _).map(pf). What I don't understand is what just .collect() does. Can anyone explain this?
collect without parameters fetches all data stored in a RDD to the driver.
Return an array that contains all of the elements in this RDD.
Note
This method should only be used if the resulting array is expected to be small, as all the data is loaded into the driver's memory.
There is no connection to the version with PartialFunction whatsoever. Both are used for completely different things.
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I have a problem with a stored procedure.
The procedure gets as an argument the number of rows needed, but the following does not work in HANA:
SELECT TOP :NUM_OF_ROWS * FROM TABLE_NAME
I read that TOP in HANA only receives a number, not an expression. Is there another way to do this? My solution for the moment is to select everything and delete the unneeded records on the service, but it's not very efficient.
Instead of TOP n you can use the LIMIT n option.
That one can bind variables.
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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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Scala uses a type-system based on System F ω, which is normally said to be strongly normalizing. Strongly normalizing implies non-Turing completeness.
Nevertheless, Scala's type-system is Turing-complete.
Which changes/additions/modifications make Scala's type-system Turing-complete compared to the formal algorithms and systems?
It's not a comprehensive answer but the reason is that you can define recursive types.
I've asked similar questions before (about what a non-Turing complete language might look like). The answers were of the form: a Turing complete language must support either arbitrary looping or recursion. Scala's type system supports the latter