Evictor | Java library providing a concurrent map | iOS library
kandi X-RAY | Evictor Summary
kandi X-RAY | Evictor Summary
The central abstraction is the interface ConcurrentMapWithTimedEviction, which extends ConcurrentMap by adding the following four methods:. In the above methods, evictMs is the time in milliseconds during which the entry can stay in the map (time-to-live). When this time has elapsed, the entry will be evicted from the map automatically. A value of 0 means "forever". There is a single implementation of this interface, ConcurrentMapWithTimedEvictionDecorator, which decorates an existing ConcurrentMap implementation, and one convenient subclass, ConcurrentHashMapWithTimedEviction which conforms to the ConcurrentHashMap specification and is easier to use than its superclass if a ConcurrentHashMap is what you want. These two classes can be customized with different eviction schedulers, which is an abstraction for the actual mechanism to automatically evict entries upon expiration. In addition, some of the schedulers are based on a priority queue and can be additionally customized by using different priority queue implementations.
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Top functions reviewed by kandi - BETA
- Checks whether the map contains the given value
- Removes the entry if it is expired
- Removes an entry from the delegate
- Cancel the automatic eviction
- Removes the entry associated with the specified key from the delegate map
- Schedules an eviction task
- Sets the additional data associated with this entry
- Evicts entries from the map
- Attempts to evict the entry from the map
- Removes the mapping associated with the specified key from this map
- Removes all the mappings from this map
- Evicts all the entries in the queue
- Shutdown the Scheduler
- Checks if the task has been scheduled
- Attempts to cancel the eviction
- Shuts the scheduled executor service
- Returns the expiration time
- Returns true if the map contains a mapping for the given key
- Returns the next eviction time
- Cancel eviction
- Evict the queue
- Stops the eviction thread
- Returns the value associated with the specified key
- Schedules the next eviction time
- Cancels the eviction
- Schedules an eviction entry
Evictor Key Features
Evictor Examples and Code Snippets
Lines of Code : 20License : Permissive (Apache-2.0)
Copy// Create hash map with default initial capacity, load factor, number of threads,
// and eviction scheduler
// An instance of SingleThreadEvictionScheduler is used in this case
ConcurrentMapWithTimedEviction map =
new ConcurrentHashMapWithTimedE // Create a concurrent hash map with Guava
ConcurrentMap> delegate =
new MapMaker().makeMap();
// Create a map with a SingleThreadEvictionScheduler
EvictionScheduler scheduler = new SingleThreadEvictionScheduler<>();
ConcurrentMapWithTi V put(K key, V value, long evictMs);
V putIfAbsent(K key, V value, long evictMs);
V replace(K key, V value, long evictMs);
boolean replace(K key, V oldValue, V newValue, long evictMs);
Community Discussions
Trending Discussions on Evictor
QUESTION
We have an Apache Flink application which processes events
- The application uses event time characteristics
- The application shards (
keyBy) events based on thesessionIdfield - The application has windowing with 1 minute tumbling window
- The windowing is specified by a
reduceand aprocessfunctions - So, for each session we will have 1 computed record
- The windowing is specified by a
- The application emits the data into a Postgres sink
Application:
- It is hosted in AWS via Kinesis Data Analytics (KDA)
- It is running in 5 different regions
- The exact same code is running in each region
Database:
- It is hosted in AWS via RDS (currently it is a PostgreSQL)
- It is located in one region (with a read replica in a different region)
Because we are using event time characteristics with 1 minute tumbling window all regions' sink emit their records nearly at the same time.
What we want to achieve is to add artificial delay between window and sink operators to postpone sink emition.
Flink App Offset Window 1 Sink 1st run Window 2 Sink 2nd run #1 0 60 60 120 120 #2 12 60 72 120 132 #3 24 60 84 120 144 #4 36 60 96 120 156 #5 48 60 108 120 168 Not working work-aroundWe have thought that we can add some sleep to evictor's evictBefore like this
ANSWER
Answered 2022-Mar-07 at 16:03You could use TumblingEventTimeWindows of(Time size, Time offset, WindowStagger windowStagger) with WindowStagger.RANDOM.
See https://nightlies.apache.org/flink/flink-docs-stable/api/java/org/apache/flink/streaming/api/windowing/assigners/WindowStagger.html for documentation.
QUESTION
I am able to start the server with the command line 'java -jar jarname.jar But , while running main method of the spring boot application , server start fails ,saying that a class from an imported dependency project does not exists
...ANSWER
Answered 2021-Nov-28 at 13:45Instead of a multi-module project, make it as a single module project or specify appropriately in the manifest.
QUESTION
I'm trying to use Flink to consume a bounded data from a message queue in a streaming passion. The data will be in the following format:
...ANSWER
Answered 2021-Nov-04 at 08:56There are a couple of things getting in the way of what you want:
(1) Flink's window operators produce append streams, rather than update streams. They're not designed to update previously emitted results. CEP also doesn't produce update streams.
(2) Flink's file system abstraction does not support overwriting files. This is because object stores, like S3, don't support this operation very well.
I think your options are:
(1) Rework your job so that it produces an update (changelog) stream. You can do this with toChangelogStream, or by using Table/SQL operations that create update streams, such as GROUP BY (when it's used without a time window). On top of this, you'll need to choose a sink that supports retractions/updates, such as a database.
(2) Stick to producing an append stream and use something like the FileSink to write the results to a series of rolling files. Then do some scripting outside of Flink to get what you want out of this.
QUESTION
I have a flink job that process Metric(name, type, timestamp, value) Object. Metrics are keyby (name, type, timestamp). I am trying to process metrics with specific timestamp starting timestamp + 50 second. Every timestamp has interval of 10 second. I am currently trying window(SlidingEventTimeWindows.of(Time.seconds(50), Time.seconds(10))) with a ProcessWindowFunction with
ANSWER
Answered 2021-Jul-26 at 00:41The reason why you are not getting more events in each window is that you have included the timestamp in the key. This has the effect of forcing each window to only include events that all have the same timestamp.
QUESTION
This is a really odd error that I am getting while doing a maven build. I am encountering an error like this:
...ANSWER
Answered 2021-Jun-29 at 13:28I feel really silly about this now. It turns out someone uploaded something to our internal artifactory for commons-lang that was not really commons-lang. No idea how that happened, but it was a never-ending source of frustration for me. If anyone else ever sees something that doesn't make sense like this, compare the size of the jar in your .m2 folder with one downloaded directly from maven central. That would have saved me a lot of time.
QUESTION
I'm using Flink DataStreams to join 2 streams (a Book stream and a Publisher stream). I'm trying to remove elements by using evictor in case they are deleted from the database, which is indicated with the variable deleted.
When I run the code without the evictor it works well, but when I add the evictor it fails.
ANSWER
Answered 2021-Apr-30 at 20:27The problem is most likely that your enclosing class (AuthorIndex presumably) is not serializable and your program is trying to serialize it. This can be avoided by creating a separate class instead of using an anonymous class or making the method static.
QUESTION
Before anyone mark this as a duplicate, I referenced this stackoverflow question before posting here, I tried all solutions in that thread but still it is not working for me. I am migrating a legacy java project into spring boot application. When I start the server I am getting this stacktrace,
...ANSWER
Answered 2021-Apr-08 at 15:49This might have to do with you not using Generics with your java Collections
QUESTION
I was following this guide which mentions that the @EnableAuthorizationServer is deprecated. But when I created a project with the following dependencies, I am not getting the deprecated messages. Is there something I am missing here.
Depedencies - Output from mvn dependency:tree
ANSWER
Answered 2021-Jan-07 at 14:28Well the correct term is that @EnableAuthorizationServer is in maintenance mode which basically means deprecated. As in there will be no added features or updates.
The story goes basically as follows.
During Spring 4 i believe there was a single person that maintained the oauth2 part of spring security. When Spring security 5 was launched the team at pivotal decided to do a major overhaul of spring security and the oauth2 parts. So what they did was to drop Authorisation server support, and instead focus on the Resource server support at first.
Spring announcement of dropping Authorisation server support
You have pulled in spring-cloud-starter-oauth2 which in turn har a peer dependency on spring-security-oauth2-autoconfigure which in turn pulls in spring-security-oauth2.
Here Spring clearly states that if you wish to use spring-security-oauth2 they will help you out, but it is in maintenance mode.
The choice to not support it was made because an authorization server is like owning a product. Spring doesn't maintain their own database, or own Ldap server etc. There are plenty of auth servers out there that can be used, okta, curity, github, fb, google, etc, etc.
But Spring has actually reevaluated that choice and decided to start a community developed open source authorisation server
So you have 3 choices:
- use the old, that is in maintenance mode
- use a 3rd party vendor, github, fb, google, okta, curity etc.
- try out the new open source authorisation server
QUESTION
I'm programming a little app via Android Studio. I'm working with 2 activities. My app stops responding as soon as my first activity opens the second one (When I'm running the app through the emulator). I realized that the problem first appeared as I inserted the for loop in my second activity. But the audio output of the notes is still done in the background.
Would be very nice if you could help me here.
Here the code:
...ANSWER
Answered 2020-Nov-12 at 13:55You are running
QUESTION
I have two streams in Flink stream1 has 70000 records per sec and stream2 may or may not have data.
ANSWER
Answered 2020-Oct-08 at 10:51I believe the problem is that the lack of watermarks from the idle stream is holding back the overall watermark. Whenever multiple streams are connected, the resulting watermark is the minimum of the incoming watermarks. This can then lead to problems like the one you are experiencing.
You have a couple of options:
- Set the watermark for
stream2to beWatermark.MAX_WATERMARK, thereby givingstream1complete control of watermarking. - Somehow detect that
stream2is idle, and artificially advance the watermark despite the lack of events. Here is an example.
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