I just tested putting something in an AppFabric cache, and I'm struggling now with how to simply view the items in the cache. Surprisingly, google hasn't helped. In PowerShell, I can view the caches easily enough with get-cache.
What PowerShell command is there to view the items in a cache?
There isn't one.
And if you think about it, there can't be one - what would it output? If you have simple values like strings or integers in your cache, then it's reasonably clear that you could just iterate over the cache outputting the key-value pairs. But if you have complex (and potentially nested) objects in your cache, or maybe a List containing a large number of objects, what do you output then? The key and the type? Some kind of Id property that may or may not exist?
There can't be a one-size-fits-all Powershell command that Microsoft could supply out of the box to do this that would cope with any kind of object it might encounter in the cache.
Related
I was wondering if I can use the here-api to geocode addresses (bulk way) and store the results. I need to store them on a python data frame to afterwards merge them with a shape file. However, in the TOS HERE says that you cannot store the results from geocoding.
I've been in your situation. Let me list the options that we've considered.
You could fetch address information dynamically using their Geocoding API. Advantage is that you'll always have up-to-date information, and you don't need to query places that you'll never use anyway.
I'm assuming that your shape file is based on HERE data. You could still try to use OpenStreetMaps. You'll get some inaccuracies if the map data differs, but it's free, and not as restrictive as HERE.
You could opt to buy the HERE map data, to work around the TOS restrictions
By the way, we went for an option 4: switching to OpenStreetMaps entirely, but it sounds like you don't have that luxery, because you have to work with existing shapefiles that you want to "enrich".
Basically I'm trying to run some code (Python 2.7) if the content on a website changes, otherwise wait for a bit and check it later.
I'm thinking of comparing hashes, the problem with this is that if the page has changed a single byte or character, the hash would be different. So for example if the page display the current date on the page, every single time the hash would be different and tell me that the content has been updated.
So... How would you do this? Would you look at the Kb size of the HTML? Would you look at the string length and check if for example the length has changed more than 5%, the content has been "changed"? Or is there some kind of hashing algorithm where the hashes stay the same if only small parts of the string/content has been changed?
About last-modified - unfortunately not all servers return this date correctly. I think it is not reliable solution. I think better way - combine hash and content length solution. Check hash, and if it changed - check string length.
There is no universal solution.
Use If-modifed-since or HEAD when possible (usually ignored by dynamic pages)
Use RSS when possible.
Extract last modification stamp in site-specific way (news sites have publication dates for each article, easily extractable via XPATH)
Only hash interesting elements of page (build site-specific model) excluding volatile parts
Hash whole content (useless for dynamic pages)
Safest solution:
download the content and create a hash checksum using SHA512 hash of content, keep it in the db and compare it each time.
Pros: You are not dependent to any Server headers and will detect any modifications.
Cons: Too much bandwidth usage. You have to download all the content every time.
Using Head
Request page using HEAD verb and check the Header Tags:
Last-Modified: Server should provide last time page generated or Modified.
ETag: A checksum-like value which is defined by server and should change as soon as content changed.
Pros: Much less bandwidth usage and very quick update.
Cons: Not all servers provides and obey following guidelines. Need to get real resource using GET request if you find data is need to fetch
Using GET
Request page using GET verb and using conditional Header Tags:
* If-Modified-Since: Server will check if resource modified since following time and return content or return 304 Not Modified
Pros: Still Using less bandwidth, Single trip to receive data.
Cons: Again not all resource support this header.
Finally, maybe mix of above solution is optimum way for doing such action.
If you're trying to make a tool that can be applied to arbitrary sites, then you could still start by getting it working for a few specific ones - downloading them repeatedly and identifying exact differences you'd like to ignore, trying to deal with the issues reasonably generically without ignoring meaningful differences. Such a quick hands-on sampling should give you much more concrete ideas about the challenge you face. Whatever solution you attempt, test it against increasing numbers of sites and tweak as you go.
Would you look at the Kb size of the HTML? Would you look at the string length and check if for example the length has changed more than 5%, the content has been "changed"?
That's incredibly rough, and I'd avoid that if at all possible. But, you do need to weigh up the costs of mistakenly deeming a page unchanged vs. mistakenly deeming it changed.
Or is there some kind of hashing algorithm where the hashes stay the same if only small parts of the string/content has been changed?
You can make such a "hash", but it's very hard to tune the sensitivity to meaningful change in the document. Anyway, as an example: you could sort the 256 possible byte values by their frequency in the document and consider that a 2k hash: you can later do a "diff" to see how much that byte value ordering's changed in a later download. (To save memory, you might get away with doing just the printable ASCII values, or even just letters after standardising capitalisation).
An alternative is to generate a set of hashes for different slices of the document: e.g. dividing it into header vs. body, body by heading levels then paragraphs, until you've got at least a desired level of granularity (e.g. 30 slices). You can then say that if only 2 slices of 30 have changed you'll consider the document the same.
You might also try replacing certain types of content before hashing - e.g. use regular expression matching to replace times with "<time>".
You could also do things like lower the tolerance to change more as the time since you last processed the page increases, which could lessen or cap the "cost" of mistakenly deeming it unchanged.
Hope this helps.
store the html files -- two versions..
one was the html which was taken before an hour. -- first.html
second is the html which was taken now -- second.html
Run the command :
$ diff first.html second.html > diffs.txt
If the diffs has some text then the file is changed.
Use git, which has excellent reporting capabilities on what has changed between two states of a file; plus you won't eat up disk space as git manages the deltas for you.
You can even tell git to ignore "trivial" changes, such as adding and removing of whitespace characters to further optimize the search.
Practically what this comes down to is parsing the output of git diff -b --numstat HEAD HEAD^; which roughly translates to "find me what has changed in all the files, ignoring any whitespace changes, between the current state, and the previous state"; which will result in output like this:
2 37 en/index.html
2 insertions were made, 37 deletions were made to en/index.html
Next you'll have to do some experimentation to find a "threshold" at which you would consider a change significant in order to process the files further; this will take time as you will have to train the system (you can also automate this part, but that is another topic all together).
Unless you have a very good reason to do so - don't use your traditional, relational database as a file system. Let the operating system take care of files, which its very good at (something a relational database is not designed to manage).
You should do an HTTP HEAD request (so you don't download the file) and look at the "Last-modified" header in the response.
import requests
response = requests.head(url)
datetime_str = response.headers["last-modified"]
And keep checking if that field changes in a while loop and compare the datetime difference.
I did a little program on Python to do that:
https://github.com/javierdechile/check_updates_http
i'm working on an academic project(a search engine), the main functions of this search engine are:
1/-crawling
2/-storing
3/-indexing
4/-page ranking
all the sites that my search engine will crawl are available locally which means it's an intranet search engine.
after storing the files found by the crawler, these files need to be served quickly for caching purpose.
so i wonder what is the fastest way to store and retrieve these file ?
the first idea that came up is to use FTP or SSH, but these protocols are connection based protocols, the time to connect, search for the file and get it is lengthy.
i've already read about google's anatomy, i saw that they use a data repository, i'd like to do the same but i don't know how.
NOTES: i'm using Linux/debian, and the search engine back-end is coded using C/C++. HELP !
Storing individual files is quite easy - wget -r http://www.example.com will store a local copy of example.com's entire (crawlable) content.
Of course, beware of generated pages, where the content is different depending on when (or from where) you access the page.
Another thing to consider is that maybe you don't really want to store all the pages yourself, but just forward to the site that actually contains the pages - that way, you only need to store a reference to what page contains what words, not the entire page. Since a lot of pages will have much repeated content, you only really need to store the unique words in your database and a list of pages that contain that word (if you also filter out words that occur on nearly every page, such as "if", "and", "it", "to", "do", etc, you can reduce the amount of data that you need to store. Do a count of the number of each word on each page, and then see compare different pages, to find the pages that are meaningless to search.
Well, if the program is to be constantly running during operation, you could just store the pages in RAM - grab a gigabyte of RAM and you'd be able to store a great many pages. This would be much faster than caching them to the hard disk.
I gather from the question that the user is on a different machine from the search engine, and therefore cache. Perhaps I am overlooking something obvious here, but couldn't you just sent them the HTML over the connection already established between the user and the search engine? Text is very light data-wise, after all, so it shouldn't be too much of a strain on the connection.
I'm new to ElasticSearch, so this is probably something quite trivial, but I haven't figured out anything better that fetching everything, processing with a script and updating the registers one by one.
I want to make something like a simple SQL update:
UPDATE RECORD SET SOMEFIELD = SOMEXPRESSION
My intent is to replace the actual bogus data with some data that makes more sense (so the expression is basically randomly choosing from a pool of valid values).
There are a couple of open issues about making possible to update documents by query.
The technical challenge is that lucene (the text search engine library that elasticsearch uses under the hood) segments are read only. You can never modify an existing document. What you need to do is delete the old version of the document (which by the way will only be marked as deleted till a segment merge happens) and index the new one. That's what the existing update api does. Therefore, an update by query might take a long time and lead to issues, that's why it's not released yet. A mechanism that allows to interrupt running queries would be a nice to have too for this case.
But there's the update by query plugin that exposes exactly that feature. Just beware of the potential risks before using it.
In windows is it possible through an API to write to the middle of a file without overwriting any data and without having to rewrite everything after that?
If it's possible then I believe it will obviously fragment the file; how many times can I do it before it becomes a serious problem?
If it's not possible what approach/workaround is usually taken? Re-writing everything after the insertion point becomes prohibitive really quickly with big (ie, gigabytes) files.
Note: I can't avoid having to write to the middle. Think of the application as a text editor for huge files where the user types stuff and then saves. I also can't split the files in several smaller ones.
I'm unaware of any way to do this if the interim result you need is a flat file that can be used by other applications other than the editor. If you want a flat file to be produced, you will have to update it from the change point to the end of file, since it's really just a sequential file.
But the italics are there for good reason. If you can control the file format, you have some options. Some versions of MS Word had a quick-save feature where they didn't rewrite the entire document, rather they appended a delta record to the end of the file. Then, when re-reading the file, it applied all the deltas in order so that what you ended up with was the right file. This obviously won't work if the saved file has to be usable immediately to another application that doesn't understand the file format.
What I'm proposing there is to not store the file as text. Use an intermediate form that you can efficiently edit and save, then have a step which converts that to a usable text file infrequently (e.g., on editor exit). That way, the user can save as much as they want but the time-expensive operation won't have as much of an impact.
Beyond that, there are some other possibilities.
Memory-mapping (rather than loading) the file may provide efficiences which would speed things up. You'd probably still have to rewrite to the end of the file but it would be happening at a lower level in the OS.
If the primary reason you want fast save is to start letting the user keep working (rather than having the file available to another application), you could farm the save operation out to a separate thread and return control to the user immediately. Then you would need synchronisation between the two threads to prevent the user modifying data yet to be saved to disk.
The realistic answer is no. Your only real choices are to rewrite from the point of the modification, or build a more complex format that uses something like an index to tell how to arrange records into their intended order.
From a purely theoretical viewpoint, you could sort of do it under just the right circumstances. Using FAT (for example, but most other file systems have at least some degree of similarity) you could go in and directly manipulate the FAT. The FAT is basically a linked list of clusters that make up a file. You could modify that linked list to add a new cluster in the middle of a file, and then write your new data to that cluster you added.
Please note that I said purely theoretical. Doing this kind of manipulation under a complete unprotected system like MS-DOS would have been difficult but bordering on reasonable. With most newer systems, doing the modification at all would generally be pretty difficult. Most modern file systems are also (considerably) more complex than FAT, which would add further difficulty to the implementation. In theory it's still possible -- in fact, it's now thoroughly insane to even contemplate, where it was once almost reasonable.
I'm not sure about the format of your file but you could make it 'record' based.
Write your data in chunks and give each chunk an id.
Id could be data offset in file.
At the start of the file you could
have a header with a list of ids so
that you can read records in
order.
At the end of 'list of ids' you could point to another location in the file (and id/offset) that stores another list of ids
Something similar to filesystem.
To add new data you append them at the end and update index (add id to the list).
You have to figure out how to handle delete record and update.
If records are of the same size then to delete you can just mark it empty and next time reuse it with appropriate updates to index table.
Probably the most efficient way to do this (if you really want to do it) is to call ReadFileScatter() to read the chunks before and after the insertion point, insert the new data in the middle of the FILE_SEGMENT_ELEMENT[3] list, and call WriteFileGather(). Yes, this involves moving bytes on disk. But you leave the hard parts to the OS.
If using .NET 4 try a memory-mapped file if you have an editor-like application - might jsut be the ticket. Something like this (I didn't type it into VS so not sure if I got the syntax right):
MemoryMappedFile bigFile = MemoryMappedFile.CreateFromFile(
new FileStream(#"C:\bigfile.dat", FileMode.Create),
"BigFileMemMapped",
1024 * 1024,
MemoryMappedFileAccess.ReadWrite);
MemoryMappedViewAccessor view = MemoryMapped.CreateViewAccessor();
int offset = 1000000000;
view.Write<ObjectType>(offset, ref MyObject);
I noted both paxdiablo's answer on dealing with other applications, and Matteo Italia's comment on Installable File Systems. That made me realize there's another non-trivial solution.
Using reparse points, you can create a "virtual" file from a base file plus deltas. Any application unaware of this method will see a continuous range of bytes, as the deltas are applied on the fly by a file system filter. For small deltas (total <16 KB), the delta information can be stored in the reparse point itself; larger deltas can be placed in an alternative data stream. Non-trivial of course.
I know that this question is marked "Windows", but I'll still add my $0.05 and say that on Linux it is possible to both insert or remove a lump of data to/from the middle of a file without either leaving a hole or copying the second half forward/backward:
fallocate(fd, FALLOC_FL_COLLAPSE_RANGE, offset, len)
fallocate(fd, FALLOC_FL_INSERT_RANGE, offset, len)
Again, I know that this probably won't help the OP but I personally landed here searching for a Linix-specific answer. (There is no "Windows" word in the question, so web search engine saw no problem with sending me here.