Is there a way to do the below use case in our single query.
Check for a vertex for its existence with some id.
If exists then do the further traversals.
Currently, we are doing the above using two queries.
You shouldn't have to do anything special if your only choice is to proceed if the element exists. In other words, if you have:
g.V(1).out()
If a vertex with id of "1" is not present, it will simply not traverse out() as none exists. If you have a need for alternative processing in the event that the vertex does NOT exist then you will need to use some form of branching logic (typically coalesce() or choose()). Here's some examples of element existence checks which demonstrate "get or create" types of operations that might be applicable to what you're doing.
Related
What is the different between the validation rule exists and a custom rule that make a query to get the first record with the corresponding params in the database?
Are both the same or exists is faster and optimized?
If you go deeper into documentation you'll see what is called there.
You can find ValidatesAttributes trait that holds related methods for these rules (you can check the rest of code in Validation namespace). In code you can see it uses Exists class called in line 680.
So whether you use it as substring, array element or class it will eventually call and check against Exists class.
I am using Snap! to try to find the earliest item in a list. For instance, in list [3,1,2], I would like to report "1." I would like the solution to work for words as well (for instance, given list [Bob, George, Ari] report "Ari").
I tried to use recursion to solve the problem
and the solution works. However, I cannot find a way to do so recursively without the second "if else" statement. Is there a way to use recursion to solve this problem without the "if 0= length of..." statement?
Play with it here.
I don't see a way to do this without two if...else statements. You need two checks:
Is the list exhausted?
Is the first element less than all the following elements?
In some languages, you can use the conditional ternary operator ?:, but I don't think Snap! supports that. It's really just syntactic sugar for an if...else anyway.
You can do some clean-up on this function, though.
I recommend explicitly handling the case of a zero-length list.
"Earliest" is confusing. I recommend the term "least", since you're checking with the "less than" operator.
Don't call keep items such that [] from [] multiple times. This is inefficient and potentially a bug if someone modifies one line but forgets to modify the other. Instead, save the result in a script variable.
Don't compare the current first element to every element in the list. This gives the function an O(n^2) run time. Instead, compare it only to the least element so far. This reduces the run time to O(n).
Some of these changes are implemented here:
I am using Lucene 3.6.1. I receive a query from a user. This query may contain + or - operators, and may also contain phrases. In certain circumstances, I would like to expand the query by adding some extra terms that I compute. These terms are optional. However, any required include/exclude constraints specified by the user must be respected.
My initial strategy was to create a BooleanQuery, add a clause to it that contains the parsed user query, and then add further clauses that contain my expansion terms. The expansion terms would all be added as Occur.SHOULD. My question is how to constrain the user's query. I can imagine three possibilities:
The user's query contains no operators, which means I can include it as an Occur.SHOULD clause.
The user's query contains a + operator, so I need to include it as an Occur.MUST clause.
The user's query contains a - operator, but also other terms: Do I still include it as an Occur.MUST clause?
The question implicit in these three choices is how do I tell which condition is appropriate? I suppose I can rewrite the query and test for BooleanQuery instances, but that seems brittle.
I suppose can also try to tactic of creating a single string from the user's input and from my expansion terms, like this:
(fld1:userterm1 userterm2 -fld2:userterm3 +userterm4)^10 (fld1:expterm1)^8 (fld2:expterm2)^7 ...
Is this the best way to go? Or is there some elegant programmatic solution?
Okay, Not sure how useful this answer will be, but can't seem to come up with a hard and fast answer here, so I'll list a couple possibilities that come to mind:
First, a problem:
Modifying the query to look like:
(userquery) (other) (stuff)
I makes some sense to add the + with he rules you've shown, but a '-' prohibited term will be hard to respect correctly, since (query -prohibition) (other) will allow matches on other with prohibition present as well, and +(query -prohibition) (other) will require 'query' be matched.
The only way I see to really do that part right is to propagate the prohibited term into your automatically added terms as well, or extract it out to a parent query layer, more like (query -prohibition) --> (query) (other) -(prohibition).
And with user entered queries of arbitrary complexity, that may not be a great strategy.
If you want to tackle it by modifying the query string, then you should probably just add any terms to the end of the query. Nothing more to it.
I don't believe
(fld1:userterm1 userterm2 -fld2:userterm3 +userterm4)^10 (fld1:expterm1)^8 (fld2:expterm2)^7 ...
Is satisfactory, because userterm4 is only required within it's subquery, but a match Only on expterm1 is still acceptable. However, a query like:
fld1:userterm1 userterm2 -fld2:userterm3 +userterm4 (fld1:expterm1)^.8 (fld2:expterm2)^.7 ...
Should, I think, satisfy your needs, and prevents you from having to worry about the internals of your queryparser. I think this is the best approach.
I can also see logic in a query structured like
+(parsed userquery) (other stuff)
Effectively, always requiring a match on the user query. Lucene implicitly does this, in a sense, as it won't return a result that matches no term, even if no required fields are present in the query. This would then be using your added terms to impact scoring, rather than return a larger set of documents. This doesn't quite address what your asking, but might be worth considering.
If, despite the aforementioned problems of applying them, you still want to detect '+' and '-' operators, I think it can be reasonably assumed that a StandardQueryParser will return a BooleanQuery at base level for any query that you need to check for these operands on. You might have to worry about, for instance, DisjunctionMaxQueries, as well as what will happen when you have a simple query with an operator, like:
+myterm
I don't know if QueryParser would simply return a TermQuery, losing the plus (since it would be redundant without another term present). Concerns like that make me hesitant to address it in this way.
Similarly, attempting to detect these values from the query string must make assumptions about how things are parsed, and could become complicated.
To sumamrize, I think the best options are to, either: add terms to the end of the raw query string before doing any parsing, or treat the user query as atomic, and define the appropriate booleanclause independant of it's contents when adding to a boolean clause wrapping it with whatever other queries you need to include.
I have a list of simple regular expressions:
ABC.+DE.+FHIJ.+
.+XY.+Z.+AB
.+KLM.+NO.+J.+
QRST.+UV
they all have alternating patterns of .+ and some text (I will call "words") repeated some number of times. A pattern may or may not begin or end in .+. These regular expression are all mutually exclusive. When another regex is added I want to remove any other matching regular expressions, and add one regular expression that combines the added one with all of its matches. For example, adding:
.+J.+
would match,
ABC.+DE.+FHIJ.+
.+KLM.+NO.+J.+
and thus, these would be remove and replaced with the added regular expression resulting in:
.+J.+
.+XY.+Z.+AB
QRST.+UV
I need to store these patterns either in some data structure or (preferably) in a database in an efficient manner. I first tried a tree of dictionaries, only to realize that in the case that a regex starts with a .* it has to search the entire tree for the next word, which is order O(2^n). Unfortunately, (unless I am mistaken) it appears that neither SQLite (which I am using) nor any other relational database that I have used, supports "regular expression" as a data type. My question is, is there an efficient method for storing and retrieving such simple regular expressions? If there is no canned method, is there some data structure that would be relatively efficient (say, at worst amortized polynomial time)?
Could you please explain what you are using these regular expressions for as that would make it easier to provide a better answer? In particular when I see the way you are splitting your regular expressions I'm wondering if a Trie or a Directed acyclic word graph would be a better fit.
From their you may find your answer is as simple as providing better normalization or finding an alternative no SQL db made specifically for your problem area.
Is it possible to save variables in Prolog?
I would like to save and edit a list as the program runs but I cannot find anyway of saving the list between edits.
Probably the Prolog feature you want is assert/retract of a dynamic predicate like myListVars/1, which does nothing more than save a specified list of values that you can retrieve subsequently.
For example, if you had three variables X,Y,Z that you wanted to memorialize, they could be saved into a dynamic fact myListXYZ/1 with a predicate like this:
setListXYZ(_,_,_) :-
retract(myListXYZ(_)),
fail.
setListXYZ(X,Y,Z) :-
assert(myListXYZ([X,Y,Z])).
and retrieved with a predicate like this:
getListXYZ(X,Y,Z) :-
myListXYZ([X,Y,Z]).
This approach assumes you will only have (at most) one fact at a time for myListXYZ/1, which is guaranteed if one only accesses that predicate through the get/set pair above.
I often use similar "fact" predicates to store test cases for Prolog programs where it is inconvenient to type required arguments in manually. More than one test case can be accomodated by adding an extra argument that "labels" the test cases.