executors | C++ library for executors | Reactive Programming library

 by   chriskohlhoff C++ Version: Current License: BSL-1.0

kandi X-RAY | executors Summary

kandi X-RAY | executors Summary

executors is a C++ library typically used in Programming Style, Reactive Programming applications. executors has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

The central concept of this library is the executor. An executor embodies a set of rules about where, when and how to run a function object. For example:. Type of executor | Where, when and how ---------------- | ------------------- System | Any thread in the process. Thread pool | Any thread in the pool, and nowhere else. Strand | Not concurrent with any other function object sharing the strand, and in FIFO order. Future / Promise | Any thread. Capture any exceptions thrown by the function object and store them in the promise. Executors are ultimately defined by a set of type requirements, so the set of executors isn’t limited to those listed here. Like allocators, library users can develop custom executor types to implement their own rules. To submit a function object to an executor, we can choose from one of three fundamental operations: dispatch, post and defer. These operations differ in the eagerness with which they run the submitted function.
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            kandi-support Support

              executors has a low active ecosystem.
              It has 444 star(s) with 72 fork(s). There are 57 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 1 open issues and 0 have been closed. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of executors is current.

            kandi-Quality Quality

              executors has no bugs reported.

            kandi-Security Security

              executors has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              executors is licensed under the BSL-1.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              executors releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

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            executors Key Features

            No Key Features are available at this moment for executors.

            executors Examples and Code Snippets

            copy iconCopy
            
            	import java.util.concurrent.ExecutorService;
            	import java.util.concurrent.Executors;
            	import java.util.concurrent.Callable;
            
            	class CallableTask implements Callable {
            		private String name;
            
            		public CallableTask(String name) {
            			this.name = name;  
            Synchronizes the executors .
            pythondot img2Lines of Code : 16dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def sync_executors(self):
                """Sync both local executors and the ones on remote workers.
            
                In async execution mode, local function calls can return before the
                corresponding remote op/function execution requests are completed. Calling
                thi  
            Clear all executors associated with this context .
            pythondot img3Lines of Code : 15dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def clear_executor_errors(self):
                """Clear errors in both local executors and remote workers.
            
                After receiving errors from remote workers, additional requests on the fly
                could further taint the status on the remote workers due to the async  

            Community Discussions

            QUESTION

            How to properly use Executer In Room Android
            Asked 2021-Jun-15 at 11:44

            So I am relatively new to programming, and I have been working on this task app, where I want to save the data such as task name and more, given by the user. I am trying to accomplish this using Room. Now, initially, when I tried to do it, the app would crash since I was doing everything on the main thread probably. So, after a little research, I came to AsyncTask, but that is outdated. Now finally I have come across the Executer. I created a class for it, but I am a little unsure as to how I can implement it in my app. This is what I did :

            Entity Class :

            ...

            ANSWER

            Answered 2021-Jun-14 at 12:03

            First make a Repository class and make an instance of your DAO

            Source https://stackoverflow.com/questions/67966494

            QUESTION

            Android ExecutorService and ProgressBar
            Asked 2021-Jun-14 at 19:54

            I'm trying to implement an executorService to delete a huge Firebase node in background. This node gets a new record every ten seconds to feed a realtime linear graphic (259Krecords/month). The users need a function to clean the data from time to timen and they need to trigger it manually on demand.

            I've coded the method below:

            ...

            ANSWER

            Answered 2021-Jun-14 at 19:54

            I think I've found the problem. It happens that when I'm executing the "removeValue()" on firebase, it triggers it asynchronously. So, the for Loop is finished quite quickly giving me the LogCat above. I have added an OnSuccessListener to the remove command and am increasing the progress in there. Also, I've added a control variable in order to know when the processing is finished and thus close the progressbar. The end code, is like that:

            Source https://stackoverflow.com/questions/67943846

            QUESTION

            Additional unique index referencing columns not exposed by CDC causes exception
            Asked 2021-Jun-14 at 17:35

            I am using the SQL connector to capture CDC on a table that we only expose a subset of all columns on the table. The table has two unique indexes A & B on it. Neither index is marked as the PRIMARY INDEX but index A is logically the primary key in our product and what I want to use with the connector. Index B references a column we don't expose to CDC. Index B isn't truly used in our product as a unique key for the table and it is only marked UNIQUE as it is known to be unique and marking it gives us a performance benefit.

            This seems to be resulting in the error below. I've tried using the message.key.columns option on the connector to specify index A as the key for this table and hopefully ignore index B. However, the connector seems to still want to do something with index B

            1. How can I work around this situation?
            2. For my own understanding, why does the connector care about indexes that reference columns not exposed by CDC?
            3. For my own understanding, why does the connector care about any index besides what is configured on the CDC table i.e. see CDC.change_tables.index_name documentation
            ...

            ANSWER

            Answered 2021-Jun-14 at 17:35

            One of the contributors to Debezium seems to affirm this is a product bug https://gitter.im/debezium/user?at=60b8e96778e1d6477d7f40b5. I have created an issue https://issues.redhat.com/browse/DBZ-3597.

            Edit:

            A PR was published and approved to fix the issue. The fix is in the current 1.6 beta snapshot build.

            There is a possible workaround. The names of indices are the key to the problem. It seems they are processed in alphabetical order. Only the first one is taken into consideration so if you can rename your indices to have the one with keys first then you should get unblocked.

            Source https://stackoverflow.com/questions/67823515

            QUESTION

            Memory regarding broadcast variables in spark
            Asked 2021-Jun-14 at 17:17

            Assuming I have a cluster with two worker nodes and from these two workers, I have 10 executors. How much memory will be used up in my cluster if I choose to broadcast a 1gb Map?

            Will it be 1gb per worker so 2gb in total? Or will it be 1gb per executor so 10gb in total?

            Apologies for the simple question, but for me, a number of articles written about broadcast variables aren’t 100% clear on this issue.

            ...

            ANSWER

            Answered 2021-Jun-14 at 17:17

            Executers are the entities that perform the actual work. Each executor is its own JVM process with allotted memory.

            (As described here: http://spark.apache.org/docs/latest/cluster-overview.html)

            The broadcast is materialized at the executer level so in the above example- 10GB.

            Source https://stackoverflow.com/questions/67974064

            QUESTION

            Cannot install additional requirements to apache airflow
            Asked 2021-Jun-14 at 16:35

            I am using the following docker-compose image, I got this image from: https://github.com/apache/airflow/blob/main/docs/apache-airflow/start/docker-compose.yaml

            ...

            ANSWER

            Answered 2021-Jun-14 at 16:35

            Support for _PIP_ADDITIONAL_REQUIREMENTS environment variable has not been released yet. It is only supported by the developer/unreleased version of the docker image. It is planned that this feature will be available in Airflow 2.1.1. For more information, see: Adding extra requirements for build and runtime of the PROD image.

            For the older version, you should build a new image and set this image in the docker-compose.yaml. To do this, you need to follow a few steps.

            1. Create a new Dockerfile with the following content:

            Source https://stackoverflow.com/questions/67851351

            QUESTION

            How to write a line to end of a file every 'x' seconds
            Asked 2021-Jun-14 at 14:26

            I'm trying to write a line to a file every 5 seconds continuously. So let us say I have a String = Hello world and I run my code for 15 seconds my output should be a file containing the data

            ...

            ANSWER

            Answered 2021-Jun-14 at 13:35

            At every iteration, you re-open your file using a FileWriter. By default, it starts writing at the beginning of the file, thus overwriting its contents with always the same "Hello World" string.

            If you want to add that sentence to the end, then you want to set the "append" option when instanciating your FileWriter. Also append a line separator each time:

            Source https://stackoverflow.com/questions/67971102

            QUESTION

            Spark partition size greater than the executor memory
            Asked 2021-Jun-14 at 13:26

            I have four questions. Suppose in spark I have 3 worker nodes. Each worker node has 3 executors and each executor has 3 cores. Each executor has 5 gb memory. (Total 6 executors, 27 cores and 15gb memory). What will happen if:

            • I have 30 data partitions. Each partition is of size 6 gb. Optimally, the number of partitions must be equal to number of cores, since each core executes one partition/task (One task per partition). Now in this case, how will each executor-core will process the partition since partition size is greater than the available executor memory? Note: I'm not calling cache() or persist(), it's simply that i'm applying some narrow transformations like map() and filter() on my rdd.

            • Will spark automatically try to store the partitions on disk? (I'm not calling cache() or persist() but merely just transformations are happening after an action is called)

            • Since I have partitions (30) greater than the number of available cores (27) so at max, my cluster can process 27 partitions, what will happen to the remaining 3 partitions? Will they wait for the occupied cores to get freed?

            • If i'm calling persist() whose storage level is set to MEMORY_AND_DISK, then if partition size is greater than memory, it will spill data to the disk? On which disk this data will be stored? The worker node's external HDD?

            ...

            ANSWER

            Answered 2021-Jun-14 at 13:26

            I answer as I know things on each part, possibly disregarding a few of your assertions:

            I have four questions. Suppose in spark I have 3 worker nodes. Each worker node has 3 executors and each executor has 3 cores. Each executor has 5 gb memory. (Total 6 executors, 27 cores and 15gb memory). What will happen if: >>> I would use 1 Executor, 1 Core. That is the generally accepted paradigm afaik.

            • I have 30 data partitions. Each partition is of size 6 gb. Optimally, the number of partitions must be equal to number of cores, since each core executes one partition/task (One task per partition). Now in this case, how will each executor-core will process the partition since partition size is greater than the available executor memory? Note: I'm not calling cache() or persist(), it's simply that I'm applying some narrow transformations like map() and filter() on my rdd. >>> The number of partitions being the same of number of cores is not true. You can service 1000 partitions with 10 cores, processing one at a time. What if you have 100K partition and on-prem? Unlikely you will get 100K Executors. >>> Moving on and leaving Driver-side collect issues to one side: You may not have enough memory for a given operation on an Executor; Spark can spill to files to disk at the expense of speed of processing. However, the partition size should not exceed a maximum size, was beefed up some time ago. Using multi-core Executors failure can occur, i.e. OOM's, also a result of GC-issues, a difficult topic.

            • Will spark automatically try to store the partitions on disk? (I'm not calling cache() or persist() but merely just transformations are happening after an action is called) >>> Not if it can avoid it, but when memory is tight, eviction / spilling to disk can and will occur, and in some cases re-computation from source or last checkpoint will occur.

            • Since I have partitions (30) greater than the number of available cores (27) so at max, my cluster can process 27 partitions, what will happen to the remaining 3 partitions? Will they wait for the occupied cores to get freed? >>> They will be serviced by a free Executor at a point in time.

            • If I'm calling persist() whose storage level is set to MEMORY_AND_DISK, then if partition size is greater than memory, it will spill data to the disk? On which disk this data will be stored? The worker node's external HDD? >>> Yes, and it will be spilled to the local file system. I think you can configure for HDFS via a setting, but local disks are faster.

            This an insightful blog: https://medium.com/swlh/spark-oom-error-closeup-462c7a01709d

            Source https://stackoverflow.com/questions/67926061

            QUESTION

            Getting java.lang.ClassNotFoundException when I try to do spark-submit, referred other similar queries online but couldnt get it to work
            Asked 2021-Jun-14 at 09:36

            I am new to Spark and am trying to run on a hadoop cluster a simple spark jar file built through maven in intellij. But I am getting classnotfoundexception in all the ways I tried to submit the application through spark-submit.

            My pom.xml:

            ...

            ANSWER

            Answered 2021-Jun-14 at 09:36

            You need to add scala-compiler configuration to your pom.xml. The problem is without that there is nothing to compile your SparkTrans.scala file into java classes.

            Add:

            Source https://stackoverflow.com/questions/67934425

            QUESTION

            org.springframework.security.web.access.AccessDeniedException: Access is Denied
            Asked 2021-Jun-14 at 02:53

            dispatcher-servlet.xml

            ...

            ANSWER

            Answered 2021-Jun-14 at 02:53

            This issue is solved after correcting up my code

            Source https://stackoverflow.com/questions/67764058

            QUESTION

            CameraX Analysis / Camera onPreviewFrame
            Asked 2021-Jun-13 at 01:15

            In CameraX Analysis, setTargetResolution(new Size(2560, 800), but in Analyzer imageProxy.getImage.getWidth=1280 and getHeight=400, and YUVToByte(imageProxy.getImage).length()=768000。In Camera, parameter.setPreviewSize(2560, 800) then byte[].length in onPreviewFrame is 3072000(equales 768000*(2560/1280)*(800/400))。How can I make CameraX Analyzer imageProxy.getImage.getWidth and getHeight = 2560 and 800, and YUVToByte(ImageProxy.getImage).length()=3072000? In CameraX onPreviewFrame(), res always = null, in Camera onPreviewFrame(), res can get currect value, what's the different between CameraX and Camera? And what should I do in CameraX?

            CameraX:

            ...

            ANSWER

            Answered 2021-Jun-13 at 01:15

            With regards to the image analysis resolution, the documentation of ImageAnalysis.Builder.setTargetResolution() states that:

            The maximum available resolution that could be selected for an ImageAnalysis is limited to be under 1080p.

            So setting a size of 2560x800 won't work as you expect. In return CameraX seems to be selecting the maximum ImageAnalysis resolution that has the same aspect ratio you requested (2560/800 = 1280/400).

            Source https://stackoverflow.com/questions/67930115

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            You can download it from GitHub.

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