have always wanted to get to grips a little with Compilers and DSL's and have been trying to dabble with a SQL like engine specifically for log files.
.. I realize that there are many of these out there already, but please remember that part (well, most) of the excersize is as an excuse to learn this stuff.
I feel that I've hit a mental block though, and was hoping people could help me pass it..
Lots of the texts that I have read focus on grammar construction, which is fine - but I'm confused about the leap from having/constructing an AST to actually making it do something useful.
I have been reading the chapter in this book on interpreted languages - the one about the 'pie' language - as this seems to have the most meat about this specific part of building a language.
if I had to code something like
select x,y from "c:\temp\foo.txt" where x=1 delimited by {Commas}
Assume I have loaded the contents of the file into an ArrayList to make things easy, Then would I be building an external tree walker to traverse my AST and shuffle elements into intermediate storage (if they matched x=1) - finally printing out the last buffer which would be the result set.
Looking forward to any guidance on offer.
Cheers, Ace
Related
I do not have control of how this data is stored (I know as normalized data would be better for sql), because it is saved via the WordPress GravityForms plugin. The plugin uses a serialized array to define the question id (field_id), question label (label). My goal is to extract these three values in the following format:
field_id label
1 1. I know my organization’s mission (what it is trying to accomplish).
2 2. I know my organization’s vision (where it is trying to go in the future).
Here is the serialized array.
Can anyone please provide a specific example as to how to parse these values out with sql?
A specific example, no. This kind of stuff is complex. If your are working with straight json-formatted data, here are several options, none of which are simple.
You can build your own parser. Yuck.
You can upgrade everything you have to just-released SQL 2016, and hope that the built-in json tools do what you need (I've heard iffy things about them, but don't know what their final form is like. Too, updating all your database servers right now, oh sure.)
Phil Factor over on SimpleTalk built a json T-SQL parser (https://www.simple-talk.com/sql/t-sql-programming/consuming-json-strings-in-sql-server/). It looks horrible and may run poorly, but it would do the needful.
Buried in the comments of that article are links to a CLR tool that John Galt built (at https://github.com/jgcoding/J-SQL). I have used this successfully, though I haven't done anything too complex. (If you're json is relatively simple, this could do the trick.)
There are other json parsers for SQL out there, some free, some for sale. The key thing would be to not try and write your own, but rather find and use someone else's solution that addresses your requirements.
Requirement:
I am trying to develop a language application using antlr4. The language in question is not important. The important thing is that the grammar is very vast (easily >2000 rules!!!). I want to do a number of operations
Extract bunch of informations. These can be call graphs, variable names. constant expressions etc.
Any number of transformations:
if a loop can be expanded, we go ahead and expand it
If we can eliminate dead code we might choose to do that
we might choose to rename all variable names to conform to some norms.
Each of these operations can be applied independent of each other. And after application of these steps I want the rewrite the input as close as possible to the original input.
e.g. So we might want to eliminate loops and rename the variable and then output the result in the original language format.
Questions:
I see a need to build a custom Tree (read AST) for this. So that I can modify the tree with each of the transformations. However when I want to generate the output, I lose the nice abilities of the TokenStreamRewriter. I have to specify how to write each of the nodes of the tree and I lose the original input formatting for the places I didn't do any transformations. Does antlr4 provide a good way to get around this problem?
Is AST the best way to go? Or do I build my own object representation? If so how do I create that object efficiently? Creating object representation is very big pain for such a vast language. But may be better in the long run. Again how do I get back the original formatting?
Is it possible to work just on the parse tree?
Are there similar language applications which do the same thing? If so what strategy do they use?
Any input is welcome.
Thanks in advance.
In general, what you want is called a Program Transformation System (PTS).
PTSs generally have parsers, build ASTs, can prettyprint the ASTs to recover compilable source text. More importantly, they have standard ways to navigate/inspect/modify the ASTs so that you can change them programmatically.
Many offer these capabilities in the form of pattern-matching code fragments written in the surface syntax of the language being transformed; this avoids the need to forever having to know excruciatingly fine details about which nodes are in your AST and how they are related to children. This is incredibly useful when you big complex grammars, as most of our modern (and our legacy languages) all seem to have.
More sophisticated PTSs (very few) provide additional facilities for teasing out the semantics of the source code. It is pretty hard to analyze/transform most code without knowing what scopes individual symbols belong to, or their type, and many other details such as data flow. Full disclosure: I build one of these.
A wise man told me that to learn how a syntax works does not mean your a good programmer, but rather to grasp programming constructs like iterators and conditionals, thus, meaning you can pick up any syntax easier.
How would one go about learning these constructs??
The easiest construct you mention is a conditional.
The basic pattern of a conditional is:
if <some-condition> then
<do-action>
else
<do-other-action>
end if
This basic pattern is expressed in many different ways according to the language of choice, but is the basic decision-making building block of any program.
An iterator is a construct which abstracts the physical layout of a data structure, allowing you to iterate (pass through) it without worrying about where in memory each element in the data structure is.
So, for example, you can define a data structure such as any of Array, Vector, Deque, Linked List, etc.
When you go to iterate, or pass through the data structure one element at a time, the iterator presents you with an interface in which each element in the data structure follows sequentially, allowing you to loop through with a basic for loop structure:
for <element> in <data-structure>
<do-action>
end loop
As for other constructs, take a look at some books on Data Structures and Algorithms (usually a 2nd-year level computer science course).
Syntax is only a technical form of expressing your solution. The way you implement and the concepts you use in your solution are the ones who makes the different between a beginner and an experienced developer. Programming languages are the means not the wits !
What's the best way to store and search a database of natural language sentence structure trees?
Using OpenNLP's English Treebank Parser, I can get fairly reliable sentence structure parsings for arbitrary sentences. What I'd like to do is create a tool that can extract all the doc strings from my source code, generate these trees for all sentences in the doc strings, store these trees and their associated function name in a database, and then allow a user to search the database using natural language queries.
So, given the sentence "This uploads files to a remote machine." for the function upload_files(), I'd have the tree:
(TOP
(S
(NP (DT This))
(VP
(VBZ uploads)
(NP (NNS files))
(PP (TO to) (NP (DT a) (JJ remote) (NN machine))))
(. .)))
If someone entered the query "How can I upload files?", equating to the tree:
(TOP
(SBARQ
(WHADVP (WRB How))
(SQ (MD can) (NP (PRP I)) (VP (VB upload) (NP (NNS files))))
(. ?)))
how would I store and query these trees in a SQL database?
I've written a simple proof-of-concept script that can perform this search using a mix of regular expressions and network graph parsing, but I'm not sure how I'd implement this in a scalable way.
And yes, I realize my example would be trivial to retrieve using a simple keyword search. The idea I'm trying to test is how I might take advantage of grammatical structure, so I can weed-out entries with similar keywords, but a different sentence structure. For example, with the above query, I wouldn't want to retrieve the entry associated with the sentence "Checks a remote machine to find a user that uploads files." which has similar keywords, but is obviously describing a completely different behavior.
Relational databases cannot store knowledge in a natural way, what you actually need is a knowledge base or ontology (though it may be constructed on top of relational database). It holds data in triplets <subject, predicate, object>, so your phrase will be stored as <upload_file(), upload, file>. There's a lot of tools and methods to search inside such KBs (for example, Prolog is a language that was designed to do it). So, all you have to do is to translate sentences from natural language to KB triplets/ontology graph, translate user query to incomplete triplets (your question will look like <?, upload, file>) or conjunctive queries and then search on your KB. OpenNLP will help you with translating, and the rest depends on concrete technique and technologies you decide to use.
I agree with ffriend that you need to take a different approach that builds on existing work on knowledge bases and natural language search. Storing context-free parse trees in a relational database isn't the problem, but it is going to be very difficult to do a meaningful comparison of parse trees as part of a search. When you are just interested taking advantage of a little knowledge about grammatical relations, parse trees are really too complicated. If you simplify the parse into dependency triples, you can make the search problem much easier and get at the grammatical relations you were interested in in the first place. For instance, you could use the Stanford dependency parser, which generates a context-free parse and then extracts dependency triples from it. It produces output like this for "This function uploads files to a remote machine":
det(function-2, This-1)
nsubj(uploads-3, function-2)
dobj(uploads-3, files-4)
det(machine-8, a-6)
amod(machine-8, remote-7)
prep_to(uploads-3, machine-8)
In your database, you could store a simplified subset of these triples associated with the function, e.g.:
upload_file(): subj(uploads, function)
upload_file(): obj(uploads, file)
upload_file(): prep(uploads, machine)
When people search, you can find the function that has the most overlapping triples or something along those lines, where you probably also want to weight the different dependency relations or allow partial matches, etc. You probably also want to reduce the words in the triples to lemmas, maybe POS depending on what you need.
There are plenty of people who have worked on natural language search (like Powerset), so be sure to search for existing approaches. My proposed approach here is really minimal and I can think of tons of examples where it will have problems, but I think something along these lines could work reasonably well for a restricted domain.
This is not a complete answer, but if you want to perform linguistically sophisticated queries on your trees, the best bet is to pre-process your parser output and search it with tgrep2:
http://www.stanford.edu/dept/linguistics/corpora/cas-tut-tgrep.html
Trgrep/tgrep2 are, as far as I know, the most flexible and full-featured packages for searching parse trees. This is not a MySQL-based solution as you requested, but I thought you might be interested to know about this option.
Tgrep2 allows you to ask questions about parents, descendants and siblings, whereas other solutions would not retain the full tree structure of the parse or allows such sophisticated queries.
I need to optimize code to get room for some new code. I do not have the space for all the changes. I can not use code bank switching (80c31 with 64k).
You haven't really given a lot to go on here, but there are two main levels of optimizations you can consider:
Micro-Optimizations:
eg. XOR A instead of MOV A,0
Adam has covered some of these nicely earlier.
Macro-Optimizations:
Look at the structure of your program, the data structures and algorithms used, the tasks performed, and think VERY hard about how these could be rearranged or even removed. Are there whole chunks of code that actually aren't used? Is your code full of debug output statements that the user never sees? Are there functions specific to a single customer that you could leave out of a general release?
To get a good handle on that, you'll need to work out WHERE your memory is being used up. The Linker map is a good place to start with this. Macro-optimizations are where the BIG wins can be made.
As an aside, you could - seriously- try rewriting parts of your code with a good optimizing C compiler. You may be amazed at how tight the code can be. A true assembler hotshot may be able to improve on it, but it can easily be better than most coders. I used the IAR one about 20 years ago, and it blew my socks off.
With assembly language, you'll have to optimize by hand. Here are a few techniques:
Note: IANA8051P (I am not an 8501 programmer but I have done lots of assembly on other 8 bit chips).
Go through the code looking for any duplicated bits, no matter how small and make them functions.
Learn some of the more unusual instructions and see if you can use them to optimize, eg. A nice trick is to use XOR A to clear the accumulator instead of MOV A,0 - it saves a byte.
Another neat trick is if you call a function before returning, just jump to it eg, instead of:
CALL otherfunc
RET
Just do:
JMP otherfunc
Always make sure you are doing relative jumps and branches wherever possible, they use less memory than absolute jumps.
That's all I can think of off the top of my head for the moment.
Sorry I am coming to this late, but I once had exactly the same problem, and it became a repeated problem that kept coming back to me. In my case the project was a telephone, on an 8051 family processor, and I had totally maxed out the ROM (code) memory. It kept coming back to me because management kept requesting new features, so each new feature became a two step process. 1) Optimize old stuff to make room 2) Implement the new feature, using up the room I just made.
There are two approaches to optimization. Tactical and Strategical. Tactical optimizations save a few bytes at a time with a micro optimization idea. I think you need strategic optimizations which involve a more radical rethinking about how you are doing things.
Something I remember worked for me and could work for you;
Look at the essence of what your code has to do and try to distill out some really strong flexible primitive operations. Then rebuild your top level code so that it does nothing low level at all except call on the primitives. Ideally use a table based approach, your table contains stuff like; Input state, event, output state, primitives.... In other words when an event happens, look up a cell in the table for that event in the current state. That cell tells you what new state to change to (optionally) and what primitive(s) (if any) to execute. You might need multiple sets of states/events/tables/primitives for different layers/subsystems.
One of the many benefits of this approach is that you can think of it as building a custom language for your particular problem, in which you can very efficiently (i.e. with minimal extra code) create new functionality simply by modifying the table.
Sorry I am months late and you probably didn't have time to do something this radical anyway. For all I know you were already using a similar approach! But my answer might help someone else someday who knows.
In the whacked-out department, you could also consider compressing part of your code and only keeping some part that is actively used decompressed at any particular point in time. I have a hard time believing that the code required for the compress/decompress system would be small enough a portion of the tiny memory of the 8051 to make this worthwhile, but has worked wonders on slightly larger systems.
Yet another approach is to turn to a byte-code format or the kind of table-driven code that some state machine tools output -- having a machine understand what your app is doing and generating a completely incomprehensible implementation can be a great way to save room :)
Finally, if the code is indeed compiled in C, I would suggest compiling with a range of different options to see what happens. Also, I wrote a piece on compact C coding for the ESC back in 2001 that is still pretty current. See that text for other tricks for small machines.
1) Where possible save your variables in Idata not in xdata
2) Look at your Jmp statements – make use of SJmp and AJmp
I assume you know it won't fit because you wrote/complied and got the "out of memory" error. :) It appears the answers address your question pretty accurately; short of getting code examples.
I would, however, recommend a few additional thoughts;
Make sure all the code is really
being used -- code coverage test? An
unused sub is a big win -- this is a
tough step -- if you're the original
author, it may be easier -- (well, maybe) :)
Ensure the level of "verification"
and initialization -- sometimes we
have a tendency to be over zealous
in insuring we have initialized
variables/memory and sure enough
rightly so, how many times have we
been bitten by it. Not saying don't
initialize (duh), but if we're doing
a memory move, the destination
doesn't need to be zero'd first --
this dovetails with
1 --
Eval the new features -- can an
existing sub be be enhanced to cover
both functions or perhaps an
existing feature replaced?
Break up big code if a piece of the
big code can save creating a new
little code.
or perhaps there's an argument for hardware version 2.0 on the table now ... :)
regards
Besides the already mentioned (more or less) obvious optimizations, here is a really weird (and almost impossible to achieve) one: Code reuse. And with Code reuse I dont mean the normal reuse, but to a) reuse your code as data or b) to reuse your code as other code. Maybe you can create a lut (or whatever static data) that it can represented by the asm hex opcodes (here you have to look harvard vs von neumann architecture).
The other would reuse code by giving code a different meaning when you address it different. Here an example to make clear what I mean. If the bytes for your code look like this: AABCCCDDEEFFGGHH at address X where each letter stands for one opcode, imagine you would now jump to X+1. Maybe you get a complete different functionality where the now by space seperated bytes form the new opcodes: ABC CCD DE EF GH.
But beware: This is not only tricky to achieve (maybe its impossible), but its a horror to maintain. So if you are not a demo code (or something similiar exotic), I would recommend to use the already other mentioned ways to save mem.