concurrent-map | a thread-safe concurrent map for go | Map library
kandi X-RAY | concurrent-map Summary
kandi X-RAY | concurrent-map Summary
As explained here and here, the map type in Go doesn't support concurrent reads and writes. concurrent-map provides a high-performance solution to this by sharding the map with minimal time spent waiting for locks.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of concurrent-map
concurrent-map Key Features
concurrent-map Examples and Code Snippets
Lines of Code : 3License : Permissive (MIT License)
Copypublic Map listToConcurrentMap(List books) {
return books.stream().collect(Collectors.toMap(Book::getReleaseYear, Function.identity(), (o1, o2) -> o1, ConcurrentHashMap::new));
} Community Discussions
Trending Discussions on concurrent-map
QUESTION
TL;DR
What can I do to make two services (rabbitMQ consumer + HTTP server) share the same map?
More info
I'm new to Golang. Here's what I'm trying to achieve:
I have a RabbitMQ consumer receiving some json-format messages and store them into a concurrent map. On the other hand, I need an HTTP server that sends data from the concurrent map whenever a GET request arrives.
I kinda know that I need the"net/http" package for the HTTP server and the rabbitMQ client package.
However, I'm not sure how these two services can share the same map. Could anyone please offer some idea? Thank you in advance!
EDIT
One possible solution I can think of is to replace the concurrent map with Redis. So the running consumer will send the data to Redis server whenever a message arrives and then the http server will serve GET request from the data in Redis. But is there a better way to achieve my goal without adding this extra layer (Redis)?
...ANSWER
Answered 2021-Mar-21 at 19:35Assuming that your two "services" live inside the same Go program, dependency injection. You can define a type that wraps your map (or provides equivalent functionality), instantiate it when your application starts, and inject it into both the HTTP handler and the MQ consumer.
The following code is meant to illustrate the concept:
QUESTION
I have a program which uses a lot of std::map structures. Now I want to use them with with multiple threads and assume that inserting or deleting keys will potentially alter the whole data structure and break it in parallel. But when I do not add new keys, it should be fine, right?
The following program shows what I want to do:
...ANSWER
Answered 2019-Nov-04 at 14:48EDIT:
There is no standard guarantee it will work properly since operator[] is not guaranteed to not modify the structure. Instead at() or find() would be better choices.
As far as I understand C++ standard and OpenMP docs - this is safe. Firstly, as long as you don't make operations modifying iterators the parallel modification should be fine.
Second question is if the data written in different threads will be visible in other threads. Luckily OpenMP has pretty good documentation which states that memory sync happens implicitly:
At exit from the task region of each implicit task;
QUESTION
I have the following line of code:
...ANSWER
Answered 2019-Dec-11 at 22:19sync.Map is not a Go map, and so you cannot using the a_map["key"] syntax with it. Rather, it is a struct with methods providing the usual map operations. The syntax for using it is:
QUESTION
I'm trying to build the teamcity prometheus exporter I found in this repo.
In the readme it instructs me to execute the following command which should build the project -
docker run --rm -v "$PWD":/go/src/github.com/guidewire/teamcity_exporter -w /go/src/github.com/guidewire/teamcity_exporter -e GOOS=linux -e GOARCH=amd64 golang:1.8 go build -o bin/teamcity_exporter -v
But it fails with the following error -
...ANSWER
Answered 2018-Nov-16 at 18:36I would recommend changing go build to go get. That should fetch all the dependencies and will also build the binary and drop it into $GOPATH/bin. go build expects everything to already be in place.
QUESTION
I am joining a small table to a huge table in Spark using SparkSQL. I am having the problem that my local disks are being filled by the shuffle writes about halfway through the join.
Is there a Spark setting that I can use to spill shuffle data not to local disk but to our hdfs storage (large Isilon cluster)?
Is there some other way to make a join where the output is larger than my combined local disk storage?
I have made sure that both input tables are partitioned and that the output table is partitioned.
I do not care about performance of the query, I just want it to finish without crashing.
DetailsI am running Spark 1.5.1. I am also open to attempting using hive, but my experience tells me that this crashes even faster.
For more details on my cluster you can also see this question.
...ANSWER
Answered 2017-Apr-27 at 08:52I think you can storage your results in hdfs,but can't put the data computing to hdfs. Because the computation must occur on memory or on disk.
QUESTION
I came across the following example on winterbe.com which is demonstrating the use of Atomic variables.
...ANSWER
Answered 2018-Jan-23 at 10:06The JavaDoc for shutdownNow says:
Attempts to stop all actively executing tasks, halts the processing of waiting tasks, and returns a list of the tasks that were awaiting execution.
This method does not wait for actively executing tasks to terminate. Use awaitTermination to do that.
So this does not wait for all the tasks you have submitted to finish, so just get the results for the threads that did manage to run.
To shutdown the service and wait for everything to finish replace the shutdownNow with something like:
QUESTION
Code first:
...ANSWER
Answered 2017-Apr-13 at 11:52You have to change your code as shown below:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install concurrent-map
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
