data-streaming | Stream Processing library
kandi X-RAY | data-streaming Summary
kandi X-RAY | data-streaming Summary
该项目为 MeterSphere 配套的 Data-Streaming 组件，该组件用于收集性能测试的结果数据并计算生成性能测试报告。.
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Top functions reviewed by kandi - BETA
- Returns statistics for a report
- Gets the statistics
- Executes the reportRealtime action
- Execute the report
- Handle average bandwidth calculation
- Handles average transactions
- Initialize consumer list
- Create a filter based on date range
- Computes report
- Compute sample report
- Zips the given data
- Parse summary
- Intercepts the invocation
- Save file
- Get report time info
- Consume a Kafka listener
- Get summary action
- Perform errors action
- Main entry point
- Execute report
- Gets report action
- Returns the error counts for a report
- Unzip a zip
- Get all action subclasses
- Consume a Kafka topic
- Execute summary action
data-streaming Key Features
data-streaming Examples and Code Snippets
Community Discussions
Trending Discussions on data-streaming
QUESTION
We are using stream ingestion from Event Hubs to Azure Data Explorer. The Documentation states the following:
The streaming ingestion operation completes in under 10 seconds, and your data is immediately available for query after completion.
I am also aware of the limitations such as
Streaming ingestion performance and capacity scales with increased VM and cluster sizes. The number of concurrent ingestion requests is limited to six per core. For example, for 16 core SKUs, such as D14 and L16, the maximal supported load is 96 concurrent ingestion requests. For two core SKUs, such as D11, the maximal supported load is 12 concurrent ingestion requests.
But we are currently experiencing ingestion latency of 5 minutes (as shown on the Azure Metrics) and see that data is actually available for quering 10 minutes after ingestion.
Our Dev Environment is the cheapest SKU Dev(No SLA)_Standard_D11_v2 but given that we only ingest ~5000 Events per day (per metric "Events Received") in this environment this latency is very high and not usable in the streaming scenario where we need to have the data available < 1 minute for queries.
Is this the latency we have to expect from the Dev Environment or are the any tweaks we can apply in order to achieve lower latency also in those environments? How will latency behave with a production environment loke Standard_D12_v2? Do we have to expect those high numbers there as well or is there a fundamental difference in behavior between Dev/test and Production Environments in this concern?
...ANSWER
Answered 2021-Jun-15 at 08:34Did you follow the two steps needed to enable the streaming ingestion for the specific table, i.e. enabling streaming ingestion on the cluster and on the table?
In general, this is not expected, the Dev/Test cluster should exhibit the same behavior as the production cluster with the expected limitations around the size and scale of the operations, if you test it with a few events and see the same latency it means that something is wrong.
If you did follow these steps, and it still does not work please open a support ticket.
QUESTION
I am studying gRPC server-client programming on node runtime.
I've encountered an error in client streaming rpc. please see the following rpc method signature.
...ANSWER
Answered 2020-Jan-14 at 14:49I solved my issue. there were some problems. I will explain it.
The global variable
myTransformStreamin server.js was the problem. I moved the code intodataStreamingfunction.I also changed close, destroy option. To be detail, I turned on
autoclose,emitcloseoption infs.createReadStream(),fs.createWriteStream()and... turned onemitclose,autodestroyoption in Transform stream(myTransformStreamandmyTransform)
QUESTION
Context
There exists severals questions about how to train Word2Vec using gensim with streamed data. Anyhow, these questions don't deal with the issue that streaming cannot use multiple workers since there is no array to split between threads.
Hence I wanted to create a generator providing such functionality for gensim. My results look like:
...ANSWER
Answered 2019-Nov-12 at 16:22It seems I was too impatient. I ran the streaming-function written above which processes only one document instead of a batch:
QUESTION
I'm trying to parse the datetime to later do group by at certain hours in structured streaming.
Currently I have code like this:
...ANSWER
Answered 2019-Aug-07 at 03:51Best not to use udf because they don't use spark catalyst optimizer and especially when the spark.sql.functions modules have functions available. This code will transform your timestamp.
QUESTION
I'm using Spark 2.4.3, Scala 2.11.8, Java 1.8 and using this spark-submit --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.3 data_stream.py for job submit.
The following is the code that gives an exception (see below):
...ANSWER
Answered 2019-Aug-05 at 09:13There are a couple of things here actually. One is a kind of typo while the other is a more severe.
service_table dataframe has just a single column SERVICE_CALLS after you do kafka_df_string.select(psf.from_json(psf.col('value'), schema).alias("SERVICE_CALLS")) so you cannot service_table.select(psf.col('crime_id')) as the crime_id column does not actually exist. That was easy, wasn't it? :)
The more severe issue is with spark-submit (which is from /Users/dev/spark-2.3.0-bin-hadoop2.7 directory) while the --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.3 uses 2.4.3 for the Spark version. They simply don't match and hence the exception:
java.lang.AbstractMethodError: org.apache.spark.sql.kafka010.KafkaMicroBatchReader.createDataReaderFactories()Ljava/util/List;
Please use --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.0 (for Spark 2.3.0) to match your spark-submit and you should be fine.
QUESTION
We get this error when uploading a large file (more than 10Mb but less than 100Mb):
...ANSWER
Answered 2018-Oct-14 at 22:59The problem was indeed the credentials. Somehow the error message was very miss-leading. When we loaded the credentials explicitly the problem went away.
QUESTION
I have a maven project, which has lots of data-streaming processors and drop-wizard services.
Amongst them, are db-source - holds all the DAOs and Entities & client-source - holds external services end-points, these are used by all the apps in the project.
So far, dependency of these are individually added by each child app in their own pom and its now supposed to me moved to common versioning using on projects POM.
This is the project structure on the surface
...ANSWER
Answered 2019-May-15 at 14:34Deploy parent pom to your maven repository (or artifactory). You can try this out by doing a mvn clean install or mvn -N clean install (for parent module only) to deploy this to your local .m2
QUESTION
I'm having trouble maintaining a Bluetooth connection (from Android to a device I'm developing) for longer than a few minutes.
The scenario is:
- Device is paired successfully.
- Device transmits to Android for somewhere between 1-7 minutes (varies by device or possibly Android version).
- Android stops receiving bytes although device is still transmitting.
So: why does Android BT stop receiving?
This is very similar to the issue/observation described in bboydflo's answer to this question: Application using bluetooth SPP profile not working after update from Android 4.2 to Android 4.3
Some more background:
- The BT device I'm working with continually emits measurement packets containing ~200 characters, once per second. I am certain that the device-side is still transmitting when the issue occurs.
- This sympom happens in my app on two Android devices: an Android 5.0.1 Acer tablet, and an Android 7.1.1 Moto Play X
- I've tested with an app called Serial Bluetooth Terminal. This app does not experience the same issue; the connection is stable for as long as I've tested. Therefore, this issue is probably caused by something in my application code.
- I've seen various responses to Android BT questions directing the user to use asynchronous streams rather than polling for received bytes. This seems to be a red herring; if you feel that the threading model is causing a probelm in this case, please clearly describe why switching to async would resolve this issue.
I would like to pre-emptively address reasons that this question may be closed:
- This is not a duplicate. There are other questions on SO about BT connections dropping (i.e. Real-time Bluetooth SPP data streaming on Android only works for 5 seconds) but this is not the same issue. I have already added a keep-alive outgoing char transmitted every 1s, and my issue remains.
- I'm not asking about an issue specific to my application; at least one other user on SO has encountered this problem.
- I've reviewed the Android Bluetooth documentation in detail, and I can't see any obvious reason for this to happen.
- I'm not asking for an opinion; I'm asking for an objective answer as to why the bytes stop being received.
ANSWER
Answered 2018-Apr-24 at 19:03Ok, I have a partial answer for this one. First, a bit more background:
- I was running the BT stream polling on a thread which executed a runnable every 2s
- The buffer being used to read the stream was 1024 elements long
I had a suspicious that this might be some background buffer running out of space. So, I changed the 2s to 500ms and the 1024-length to 10024. Now, I've had about 20 minutes of connectivity without any trouble (and still going).
It would be nice to find the smoking gun for this. I initially thought that stream.Available() would be sufficient to tell if a buffer was getting filled up, but in this scenario, stream.Available() is actually returning 0 when the Android device stops receiving. So I'm not really sure which queue to check to prove that this issue is related to a buffer becoming filled.
QUESTION
I have been trying to find a connector to read data from Redis to Flink. Flink's documentation contains the description for a connector to write to Redis. I need to read data from Redis in my Flink job. In Using Apache Flink for data streaming, Fabian has mentioned that it is possible to read data from Redis. What is the connector that can be used for the purpose?
...ANSWER
Answered 2017-May-30 at 15:56There's been a bit of discussion about having a streaming redis source connector for Apache Flink (see FLINK-3033), but there isn't one available. It shouldn't be difficult to implement one, however.
QUESTION
I have a simple table as a result of the following query...
...ANSWER
Answered 2017-Aug-07 at 09:11You can write subquery which will result defined values I am assuming there would be only one defined value and non defined would be nulls so I have kept condition as "not null", then join the subset with main table to get the defined values from subset of query .
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install data-streaming
You can use data-streaming like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the data-streaming component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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