driver-java | Java driver for Hurricane
kandi X-RAY | driver-java Summary
kandi X-RAY | driver-java Summary
This is the Java driver for the the scalable, extensible, distributed messaging system called Hurricane. See the full documentation here:
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Top functions reviewed by kandi - BETA
- Sends a message to the server
- Decode a new function
- Decode a list
- Decodes an 8 - byte floating point number
- Creates a controller for the given request
- Indicates the exception
- Convert the stack trace to a string
- Returns a string representation of this object
- Returns a string representation of this response
- Compares two BitBinary objects
- Convert a list of properties to a Map
- Retrieves the route for the given request
- Compares this object with the specified object
- Read a number of bytes from the buffer
- String representation of this request
- Gets the headers
- Returns a readable representation of this object
- Compares this tuple with equality
- Sends a request to the server
- Returns a human - readable representation of this object
- Returns a string representation of this request
- Compares this object with another object
- Read a number of bytes
driver-java Key Features
driver-java Examples and Code Snippets
Community Discussions
Trending Discussions on driver-java
QUESTION
I am trying to deploy a docker container with Kafka and Spark and would like to read to Kafka Topic from a pyspark application. Kafka is working and I can write to a topic and also spark is working. But when I try to read the Kafka stream I get the error message:
...ANSWER
Answered 2022-Jan-24 at 23:36Missing application resource
This implies you're running the code using python rather than spark-submit
I was able to reproduce the error by copying your environment, as well as using findspark, it seems PYSPARK_SUBMIT_ARGS aren't working in that container, even though the variable does get loaded...
The workaround would be to pass the argument at execution time.
QUESTION
Since I upgraded Gradle, my java lib won't compile with buildconfig plugin.
Here is the build.gradle(:driver-java)
ANSWER
Answered 2021-Nov-17 at 10:36I've found a workaround, that seems to be working. I've just created an empty compile configuration.
QUESTION
I want to run a test to access the geolocation coordinates with Selenium WebDriver (version 4.0.0-rc-1):
I run this test on GitHub Actions, and it test works nice on ubuntu-latest (Ubuntu 20.04), windows-latest (Windows Server 2019), but not in macos-latest (macOS 10.15). It seems Chrome in Mac cannot access the geolocation data:
Does anybody know if it is possible to achieve it?
...ANSWER
Answered 2021-Oct-06 at 22:54I found the solution. I post here just in case it helps someone. In the macOS preferences, we need to enable location services for Chrome (System Preferences -> Security & Privacy -> Location Services), as follows:
After that, the test can access the location coordinates.
QUESTION
ANSWER
Answered 2021-Jun-21 at 21:55The AWS SDK will look in a set of predefined places to find some credentials to supply to the service when it connects. According to the Spring Boot documentation:
Spring Cloud for AWS can automatically detect this based on your environment or stack once you enable the Spring Boot property cloud.aws.region.auto.
You can also set the region in a static fashion for your application:
QUESTION
Based on the introduction in Spark 3.0, https://spark.apache.org/docs/latest/structured-streaming-kafka-integration.html. It should be possible to set "kafka.group.id" to track the offset. For our use case, I want to avoid the potential data loss if the streaming spark job failed and restart. Based on my previous questions, I have a feeling that kafka.group.id in Spark 3.0 is something that will help.
How to specify the group id of kafka consumer for spark structured streaming?
How to ensure no data loss for kafka data ingestion through Spark Structured Streaming?
However, I tried the settings in spark 3.0 as below.
...ANSWER
Answered 2020-Sep-25 at 11:18According to the Spark Structured Integration Guide, Spark itself is keeping track of the offsets and there are no offsets committed back to Kafka. That means if your Spark Streaming job fails and you restart it all necessary information on the offsets is stored in Spark's checkpointing files.
Even if you set the ConsumerGroup name with kafka.group.id, your application will still not commit the messages back to Kafka. The information on the next offset to read is only available in the checkpointing files of your Spark application.
If you stop and restart your application without a re-deployment and ensure that you do not delete old checkpoint files, your application will continue reading from where it left off.
In the Spark Structured Streaming documentation on Recovering from Failures with Checkpointing it is written that:
"In case of a failure or intentional shutdown, you can recover the previous progress and state of a previous query, and continue where it left off. This is done using checkpointing and write-ahead logs. You can configure a query with a checkpoint location, and the query will save all the progress information (i.e. range of offsets processed in each trigger) [...]"
This can be achieved by setting the following option in your writeStream query (it is not sufficient to set the checkpoint directory in your SparkContext configurations):
QUESTION
I have a Spark application which I am trying to package as a fat jar and deploy to the local cluster with spark-submit. I am using Typesafe config to create config files for various deployment environments - local.conf, staging.conf, and production.conf - and trying to submit my jar.
The command I am running is the following:
...ANSWER
Answered 2020-Nov-16 at 11:45According to Spark Docs, --files are placed in the working directory of each executor. While you're trying to access this file from driver, not executor.
In order to load config on driver side, try something like this:
QUESTION
I wrote a question here on how to simulate human-like cursor movement with Selenium Web Driver and Java.
On this quest, I discovered that Selenium Web Driver might not be the best fit. It can't move the cursor directly. Or be able to in the fashion I need.
I don't need to physically move the mouse. Just as long as the website thinks the cursor is moving normally.
I have learned about AutoIt automation and have built some scripts. I built a script to automate the Key Strokes I require when uploading a photo. I had the idea to write the file path I need to upload to a .txt file. This is done in my Java App. Then when I call my AutoIt .exe file from Java. It then reads the .txt file. Gets the file path URL. It then does the operations necessary to paste the file path. Then click the "Open" button to upload the file to the website.
Following on from this, I could save coordinates on where I want the mouse to go. In a .txt file. Then when I fire the .exe AutoIt file. It reads this .txt file and does the "human-like" mouse behavior.
I just need to know how to simulate real mouse/cursor movement in AutoIt? A function I can give some coordinates to.
I saw an article on doing in this CSS and JS... This should give you a good idea.
Can anybody help? or offer any advice? Thank you.
...ANSWER
Answered 2020-Oct-26 at 15:35Thanks to a comment made on my question. That linked to a script. It works amazingly!
It produces nonlinear mouse movements better than I ever imagined :)
QUESTION
I have gone through the following questions and pages seeking an answer for my problem, but they did not solve my problem:
Logger is not working inside spark UDF on cluster
https://www.javacodegeeks.com/2016/03/log-apache-spark.html
We are using Spark in standalone mode, not on Yarn. I have configured the log4j.properties file in both the driver and executors to define a custom logger "myLogger". The log4j.properties file, which I have replicated in both the driver and the executors, is as follows:
...ANSWER
Answered 2020-May-13 at 12:48I have resolved the logging issue. I found out that even in local mode, the logs from UDFs were not being written to the spark log files, even though they were being displayed in the console. Thus I narrowed the problem down to that the UDFs were perhaps not being able to access the file system. Then I found the following question:
How to load local file in sc.textFile, instead of HDFS
Here, there was no solution to my problem, but there was the hint that from inside Spark, if we require to refer to files, we have to refer to the root of the file system as “file:///” as seen by the executing JVM. So, I made a change in the log4j.properties file in driver:
QUESTION
My jpa application was working fine (in fact, my 2 jpa applications) since I update my mac to Catalina (and restart it, of course).
Since then I got
...ANSWER
Answered 2020-Apr-29 at 07:46Finally I got it, not sure how... probably restarting from comand line.
Here my final persistence.xml:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install driver-java
You can use driver-java 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 driver-java 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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