This issue is bugging me for some time now. To test it I just installed a fresh Apigility, set the db (PDO:mysql) and added a DB-Connected service. In the table I have 40+ records. When I make a GET collection request the response looks OK (with the default HAL content negotiation). Then I change the content negotiation to JSON. Now when I make a GET collection request my response contains only 10 elements.
So my question is: where do I set/change this limit?
You can set the page size manually, like so:
$paginator = $this->getAlbumTable()->fetchAll(true);
// set the current page to what has been passed in query string, or to 1 if none set
$paginator->setCurrentPageNumber((int) $this->params()->fromQuery('page', 1));
// set the number of items per page to 10
$paginator->setItemCountPerPage(10);
http://framework.zend.com/manual/current/en/tutorials/tutorial.pagination.html
Could you please send the page_size, total_items part at the end of the json output?
it's like:
"page_count": 140002,
"page_size": 25,
"total_items": 3500035,
"page": 1
This is not an ideal fix, because it requires you to go into the source code rather than using the page size given in the UI.
The collection class that is auto generated for you by the DB-Connected style derives off of Zend/Paginator/Paginator. This class defines the $defaultItemCountPerPage static protected member which is defaulted to 10. That's why you're only getting 10 results. If you open up the auto-generated collection class for your entity and add: protected static $defaultItemCountPerPage = 100; in the otherwise empty class, you will see that you now get up to 100 results in the response. You can look at other Paginator class variables and methods that you could replace in your derived class to get your desired behavior.
This is not an ideal solution. I'd prefer that the generated code automatically used the same configed page size that the HalJson strategy uses. Maybe I'll contribute a PR to change that. Or, maybe I'll just use the HalJson approach. It does seem like the better way to go. You should have some limit to how much data you load in from the DB at a time to not have an overly long running query or an overly large collection of data coming back you have to deal with. And, whatever limit you set, what do you do when you hit that limit? With the simple Json method, you can't ever get "page 2" of data. So, if you are going to work with some sizeable amount of data, it might be better to use HalJson on and then have some logic on the client side to grab pages of data at a time as needed. The returned JSON structure is a little more complicated, but not terribly so.
I'm probably in the same spot you are -- I'm trying to do a simple little api to play with while keeping everything simple and so I didn't want the client to have to deal with the other stuff in HalJson, but probably better to deal with that complexity and have a smooth way to page through data if you're going to use this with some real set of data. At least, that's the pep talk I'm giving myself right now. :-)
The Reference Source page for stringbuilder.cs has this comment in the ToString method:
if (chunk.m_ChunkLength > 0)
{
// Copy these into local variables so that they
// are stable even in the presence of ----s (hackers might do this)
char[] sourceArray = chunk.m_ChunkChars;
int chunkOffset = chunk.m_ChunkOffset;
int chunkLength = chunk.m_ChunkLength;
What does this mean? Is ----s something a malicious user might insert into a string to be formatted?
The source code for the published Reference Source is pushed through a filter that removes objectionable content from the source. Verboten words are one, Microsoft programmers use profanity in their comments. So are the names of devs, Microsoft wants to hide their identity. Such a word or name is substituted by dashes.
In this case you can tell what used to be there from the CoreCLR, the open-sourced version of the .NET Framework. It is a verboten word:
// Copy these into local variables so that they are stable even in the presence of race conditions
Which was hand-edited from the original that you looked at before being submitted to Github, Microsoft also doesn't want to accuse their customers of being hackers, it originally said races, thus turning into ----s :)
In the CoreCLR repository you have a fuller quote:
Copy these into local variables so that they are stable even in the presence of race conditions
Github
Basically: it's a threading consideration.
In addition to the great answer by #Jeroen, this is more than just a threading consideration. It's to prevent someone from intentionally creating a race condition and causing a buffer overflow in that manner. Later in the code, the length of that local variable is checked. If the code were to check the length of the accessible variable instead, it could have changed on a different thread between the time length was checked and wstrcpy was called:
// Check that we will not overrun our boundaries.
if ((uint)(chunkLength + chunkOffset) <= ret.Length && (uint)chunkLength <= (uint)sourceArray.Length)
{
///
/// imagine that another thread has changed the chunk.m_ChunkChars array here!
/// we're now in big trouble, our attempt to prevent a buffer overflow has been thawrted!
/// oh wait, we're ok, because we're using a local variable that the other thread can't access anyway.
fixed (char* sourcePtr = sourceArray)
string.wstrcpy(destinationPtr + chunkOffset, sourcePtr, chunkLength);
}
else
{
throw new ArgumentOutOfRangeException("chunkLength", Environment.GetResourceString("ArgumentOutOfRange_Index"));
}
}
chunk = chunk.m_ChunkPrevious;
} while (chunk != null);
Really interesting question though.
Don't think that this is the case - the code in question copies to local variables to prevent bad things happening if the string builder instance is mutated on another thread.
I think the ---- may relate to a four letter swear word...
I'm designing my back-end. I have a json array/queue/something which I only need any data that is at most 2 weeks old, that is continuously appended to. I only want to delete from this "queue", but not the container document. Can I use TTL for this, or does TTL only work for whole documents?
Is there a better way to do this? Should I store them in per-day or per-hour arrays as separate documents instead?
Running couchbase 2.2.
TTL in Couchbase only applies to whole documents, it's not possible to expire subsets of a document. Like you said you can always have separate documents with different expiry times in which you have a type,date and then the array of data as an element.
Then using a view like so:
function (doc, meta) {
if(meta.type == "json") {
if(doc.type == "ordered_data") {
if(doc.date) {
emit(dateToArray(doc.date));
}
}
}
}
You could emit all the related data ordered by date (flag descending set to true), it'd also allow your app to select specific dates by passing in one or more keys. I.e. selecting a date range of 2days,1week etc. When the document expires it'd be removed from the view when it updates (varies based upon your stale parameters plus ops a second/time).
Then you can do whatever joining or extra processing you need at the application layer. There are other options available but for me this would be the most sensible way to approach the problem, any problems just comment and we'll try again.
P.s. How big are you arrays going to become? If they are going to be very large then perhaps you'd need to look at a different tech or way to solve the problem.
I'm working with a database that holds lots of urls (tens of thousands). I'm attempting to multi-thread a resolver, that simply tries to resolve a given domain. On success, it compares the result to what's currently in the database. If it's different, the result is updated. If it fails, it's also updated.
Naturally, this will produce an inordinate volume of database calls. To clarify some of my confusion about the best way to achieve some form of asynchronous load distribution, I have the following questions (being fairly new to Perl still).
What is the best option for distributing the workload? Why?
How should I gather the urls to resolve prior to spawning?
Creating a hash of domains with the data to be compared seems to make the most sense to me. Then split it up, fire up children, children return changes to be made to parent
How should returning data to the parent be handled in a clean manner?
I've been playing with a more pythonic method (given that I have more experience in Python), but have yet to make it work due to a lack of blocking for some reason. Asside from that issue, threading isn't the best option simply due to (a lack of) CPU time for each thread (plus, I've been crucified more than once in the Perl channel for using threads :P and for good reason)
Below is more or less psuedo-code that I've been playing with for my threads (which should be used more as a supplement to my explanation of what I'm trying to accomplish, than anything).
# Create children...
for (my $i = 0; $i < $threads_to_spawn; $i++ )
{
threads->create(\&worker);
}
The parent then sits in a loop, monitoring a shared array of domains. It locks and re-populates it if it becomes empty.
Your code is the start of a persistent worker model.
use threads;
use Thread::Queue 1.03 qw( );
use constant NUM_WORKERS => 5;
sub work {
my ($dbh, $job) = #_;
...
}
{
my $q = Thread::Queue->new();
for (1..NUM_WORKERS) {
async {
my $dbh = ...;
while (my $job = $q->dequeue())
work($dbh, $job);
}
};
}
for my $job (...) {
$q->enqueue($job);
}
$q->end();
$_->join() for threads->list();
}
Performance tips:
Tweak the number of workers for your system and workload.
Grouping small jobs into larger jobs can improve speed by reducing overhead.
What is an idempotent operation?
In computing, an idempotent operation is one that has no additional effect if it is called more than once with the same input parameters. For example, removing an item from a set can be considered an idempotent operation on the set.
In mathematics, an idempotent operation is one where f(f(x)) = f(x). For example, the abs() function is idempotent because abs(abs(x)) = abs(x) for all x.
These slightly different definitions can be reconciled by considering that x in the mathematical definition represents the state of an object, and f is an operation that may mutate that object. For example, consider the Python set and its discard method. The discard method removes an element from a set, and does nothing if the element does not exist. So:
my_set.discard(x)
has exactly the same effect as doing the same operation twice:
my_set.discard(x)
my_set.discard(x)
Idempotent operations are often used in the design of network protocols, where a request to perform an operation is guaranteed to happen at least once, but might also happen more than once. If the operation is idempotent, then there is no harm in performing the operation two or more times.
See the Wikipedia article on idempotence for more information.
The above answer previously had some incorrect and misleading examples. Comments below written before April 2014 refer to an older revision.
An idempotent operation can be repeated an arbitrary number of times and the result will be the same as if it had been done only once. In arithmetic, adding zero to a number is idempotent.
Idempotence is talked about a lot in the context of "RESTful" web services. REST seeks to maximally leverage HTTP to give programs access to web content, and is usually set in contrast to SOAP-based web services, which just tunnel remote procedure call style services inside HTTP requests and responses.
REST organizes a web application into "resources" (like a Twitter user, or a Flickr image) and then uses the HTTP verbs of POST, PUT, GET, and DELETE to create, update, read, and delete those resources.
Idempotence plays an important role in REST. If you GET a representation of a REST resource (eg, GET a jpeg image from Flickr), and the operation fails, you can just repeat the GET again and again until the operation succeeds. To the web service, it doesn't matter how many times the image is gotten. Likewise, if you use a RESTful web service to update your Twitter account information, you can PUT the new information as many times as it takes in order to get confirmation from the web service. PUT-ing it a thousand times is the same as PUT-ing it once. Similarly DELETE-ing a REST resource a thousand times is the same as deleting it once. Idempotence thus makes it a lot easier to construct a web service that's resilient to communication errors.
Further reading: RESTful Web Services, by Richardson and Ruby (idempotence is discussed on page 103-104), and Roy Fielding's PhD dissertation on REST. Fielding was one of the authors of HTTP 1.1, RFC-2616, which talks about idempotence in section 9.1.2.
No matter how many times you call the operation, the result will be the same.
Idempotence means that applying an operation once or applying it multiple times has the same effect.
Examples:
Multiplication by zero. No matter how many times you do it, the result is still zero.
Setting a boolean flag. No matter how many times you do it, the flag stays set.
Deleting a row from a database with a given ID. If you try it again, the row is still gone.
For pure functions (functions with no side effects) then idempotency implies that f(x) = f(f(x)) = f(f(f(x))) = f(f(f(f(x)))) = ...... for all values of x
For functions with side effects, idempotency furthermore implies that no additional side effects will be caused after the first application. You can consider the state of the world to be an additional "hidden" parameter to the function if you like.
Note that in a world where you have concurrent actions going on, you may find that operations you thought were idempotent cease to be so (for example, another thread could unset the value of the boolean flag in the example above). Basically whenever you have concurrency and mutable state, you need to think much more carefully about idempotency.
Idempotency is often a useful property in building robust systems. For example, if there is a risk that you may receive a duplicate message from a third party, it is helpful to have the message handler act as an idempotent operation so that the message effect only happens once.
A good example of understanding an idempotent operation might be locking a car with remote key.
log(Car.state) // unlocked
Remote.lock();
log(Car.state) // locked
Remote.lock();
Remote.lock();
Remote.lock();
log(Car.state) // locked
lock is an idempotent operation. Even if there are some side effect each time you run lock, like blinking, the car is still in the same locked state, no matter how many times you run lock operation.
An idempotent operation produces the result in the same state even if you call it more than once, provided you pass in the same parameters.
An idempotent operation is an operation, action, or request that can be applied multiple times without changing the result, i.e. the state of the system, beyond the initial application.
EXAMPLES (WEB APP CONTEXT):
IDEMPOTENT:
Making multiple identical requests has the same effect as making a single request. A message in an email messaging system is opened and marked as "opened" in the database. One can open the message many times but this repeated action will only ever result in that message being in the "opened" state. This is an idempotent operation. The first time one PUTs an update to a resource using information that does not match the resource (the state of the system), the state of the system will change as the resource is updated. If one PUTs the same update to a resource repeatedly then the information in the update will match the information already in the system upon every PUT, and no change to the state of the system will occur. Repeated PUTs with the same information are idempotent: the first PUT may change the state of the system, subsequent PUTs should not.
NON-IDEMPOTENT:
If an operation always causes a change in state, like POSTing the same message to a user over and over, resulting in a new message sent and stored in the database every time, we say that the operation is NON-IDEMPOTENT.
NULLIPOTENT:
If an operation has no side effects, like purely displaying information on a web page without any change in a database (in other words you are only reading the database), we say the operation is NULLIPOTENT. All GETs should be nullipotent.
When talking about the state of the system we are obviously ignoring hopefully harmless and inevitable effects like logging and diagnostics.
Just wanted to throw out a real use case that demonstrates idempotence. In JavaScript, say you are defining a bunch of model classes (as in MVC model). The way this is often implemented is functionally equivalent to something like this (basic example):
function model(name) {
function Model() {
this.name = name;
}
return Model;
}
You could then define new classes like this:
var User = model('user');
var Article = model('article');
But if you were to try to get the User class via model('user'), from somewhere else in the code, it would fail:
var User = model('user');
// ... then somewhere else in the code (in a different scope)
var User = model('user');
Those two User constructors would be different. That is,
model('user') !== model('user');
To make it idempotent, you would just add some sort of caching mechanism, like this:
var collection = {};
function model(name) {
if (collection[name])
return collection[name];
function Model() {
this.name = name;
}
collection[name] = Model;
return Model;
}
By adding caching, every time you did model('user') it will be the same object, and so it's idempotent. So:
model('user') === model('user');
Quite a detailed and technical answers. Just adding a simple definition.
Idempotent = Re-runnable
For example,
Create operation in itself is not guaranteed to run without error if executed more than once.
But if there is an operation CreateOrUpdate then it states re-runnability (Idempotency).
Idempotent Operations: Operations that have no side-effects if executed multiple times.
Example: An operation that retrieves values from a data resource and say, prints it
Non-Idempotent Operations: Operations that would cause some harm if executed multiple times. (As they change some values or states)
Example: An operation that withdraws from a bank account
It is any operation that every nth result will result in an output matching the value of the 1st result. For instance the absolute value of -1 is 1. The absolute value of the absolute value of -1 is 1. The absolute value of the absolute value of absolute value of -1 is 1. And so on. See also: When would be a really silly time to use recursion?
An idempotent operation over a set leaves its members unchanged when applied one or more times.
It can be a unary operation like absolute(x) where x belongs to a set of positive integers. Here absolute(absolute(x)) = x.
It can be a binary operation like union of a set with itself would always return the same set.
cheers
In short, Idempotent operations means that the operation will not result in different results no matter how many times you operate the idempotent operations.
For example, according to the definition of the spec of HTTP, GET, HEAD, PUT, and DELETE are idempotent operations; however POST and PATCH are not. That's why sometimes POST is replaced by PUT.
An operation is said to be idempotent if executing it multiple times is equivalent to executing it once.
For eg: setting volume to 20.
No matter how many times the volume of TV is set to 20, end result will be that volume is 20. Even if a process executes the operation 50/100 times or more, at the end of the process the volume will be 20.
Counter example: increasing the volume by 1. If a process executes this operation 50 times, at the end volume will be initial Volume + 50 and if a process executes the operation 100 times, at the end volume will be initial Volume + 100. As you can clearly see that the end result varies based upon how many times the operation was executed. Hence, we can conclude that this operation is NOT idempotent.
I have highlighted the end result in bold.
If you think in terms of programming, let's say that I have an operation in which a function f takes foo as the input and the output of f is set to foo back. If at the end of the process (that executes this operation 50/100 times or more), my foo variable holds the value that it did when the operation was executed only ONCE, then the operation is idempotent, otherwise NOT.
foo = <some random value here, let's say -2>
{ foo = f( foo ) } curly brackets outline the operation
if f returns the square of the input then the operation is NOT idempotent. Because foo at the end will be (-2) raised to the power (number of times operation is executed)
if f returns the absolute of the input then the operation is idempotent because no matter how many multiple times the operation is executed foo will be abs(-2).
Here, end result is defined as the final value of variable foo.
In mathematical sense, idempotence has a slightly different meaning of:
f(f(....f(x))) = f(x)
here output of f(x) is passed as input to f again which doesn't need to be the case always with programming.
my 5c:
In integration and networking the idempotency is very important.
Several examples from real-life:
Imagine, we deliver data to the target system. Data delivered by a sequence of messages.
1. What would happen if the sequence is mixed in channel? (As network packages always do :) ). If the target system is idempotent, the result will not be different. If the target system depends of the right order in the sequence, we have to implement resequencer on the target site, which would restore the right order.
2. What would happen if there are the message duplicates? If the channel of target system does not acknowledge timely, the source system (or channel itself) usually sends another copy of the message. As a result we can have duplicate message on the target system side.
If the target system is idempotent, it takes care of it and result will not be different.
If the target system is not idempotent, we have to implement deduplicator on the target system side of the channel.
For a workflow manager (as Apache Airflow) if an idempotency operation fails in your pipeline the system can retry the task automatically without affecting the system. Even if the logs change, that is good because you can see the incident.
The most important in this case is that your system can retry the task that failed and doesn't mess up the pipeline (e.g. appending the same data in a table each retry)
Let's say the client makes a request to "IstanceA" service which process the request, passes it to DB, and shuts down before sending the response. since the client does not see that it was processed and it will retry the same request. Load balancer will forward the request to another service instance, "InstanceB", which will make the same change on the same DB item.
We should use idempotent tokens. When a client sends a request to a service, it should have some kind of request-id that can be saved in DB to show that we have already executed the request. if the client retries the request, "InstanceB" will check the requestId. Since that particular request already has been executed, it will not make any change to the DB item. Those kinds of requests are called idempotent requests. So we send the same request multiple times, but we won't make any change