In my spark job, each executor will initialize a c++ library which can segment a text line into word list. When two or more executors allocated on the same machine, initialization of the c++ library multiple times will cause core dump. public class TextSegment implements Serializable { private SparkSession spark = SparkSession.builder() .appName("TextSegment") .getOrCreate(); public ..
Category : apache-spark
Error: AnalysisException: Path does not exist: file:/D:/sk – Add/Main/2020/Main_2012-01.txt; Code1 with error: for i in os.listdir(): if j.endswith(‘.txt’): print(i) df= spark.read.text(i) Code2 with same err: path=r"D:sk – AddMain20" for i in os.listdir(): if j.endswith(‘.txt’): print(i) df= spark.read.text(path+”+i) Code3 without error: df1=spark.read.text(r’D:sk – AddMain20Main_2020-12.txt’) Why is it adding file:/ prefix for my file name and causing ..
I have a problem, when use yarn-client. With master=local[*] all right! I use Java 8 (jre8u202), spark on yarn – 2.4.0, on my computer – 2.3.2 (becouse 2.4.0 version on my computer do not work and i have problem: Python worker failed to connect back), pySpark – 2.3.2, Scala – 2.12.0, hadoop – 2.6. Also, ..
I have a scala/spark program that is used to validate xmls file in an input directory and then writes the report to another input parameter (local filesystem path to write report to). As per the requirements from stakeholders this program is to run on local machines hence I am using spark in local mode. Till ..
I keep having this error during installation to of spark on windows 10. "’spark-shell’ is not recognized as an internal or external command, operable program or batch file." I checked several previous questions and tried everything still having same issue. I then tried installing java jre and jdk tried both (i am not sure if ..
Jupyter notebook was installed via anaconda on windows 10. I want to run pyspark directly from notebook. For that, I used these two instructions: set PYSPARK_DRIVER_PYTHON=jupyter set PYSPARK_DRIVER_PYTHON_OPTS=notebook But when I typed: pyspark in the command line, the error message I got is: ‘jupyter’ is not recognized as an internal or external command I couldn’t ..
I have not faced this problem with any of other software on mysystem. Able to install and run everything in window terminal/command prompt and Git-Bash Recently, I started learning Spark. Installed Spark setting everything JAVA_HOME, SCALA_HOME, hadoop winutils file. Spark-shell and pyspark-shell both are running perfect in command prompt/window terminal and in Jupyter through pyspark ..
I am getting data in json format on a kafka topic. I am connecting to it via Pyspark and creating dataframe over it and doing required transformations and finally writing the dataframe in json string format in Kafka topic. But I am getting following error for that: Traceback (most recent call last): File "C:Python37-32librunpy.py", line ..
Dear users and coders, PySpark 3.0.1 and Python 3.6 Error when running a simple standalone Traceback (most recent call last): File "C:Usersbrueclipse-workspaceSPARKtest.py", line 8, in <module> sc = SparkContext(conf=conf) File "C:UsersbruAppDataLocalProgramsPythonPython36libsite-packagespysparkcontext.py", line 133, in __init__ SparkContext._ensure_initialized(self, gateway=gateway, conf=conf) File "C:UsersbruAppDataLocalProgramsPythonPython36libsite-packagespysparkcontext.py", line 325, in _ensure_initialized SparkContext._gateway = gateway or launch_gateway(conf) File "C:UsersbruAppDataLocalProgramsPythonPython36libsite-packagespysparkjava_gateway.py", line 105, in launch_gateway ..
I am installing pyspark in ubuntu wsl in windows 10. These are the commands I used after installing wsl from Microsoft Store. #install Java runtime environment (JRE) sudo apt-get install openjdk-8-jre-headless export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-amd64/jre #download spark, visit https://spark.apache.org/downloads.html if you want a different version wget https://apache.osuosl.org/spark/spark-2.4.7/spark-2.4.7-bin-hadoop2.7.tgz #untar and set a symlink sudo tar -xvzf spark-2.4.7-bin-hadoop2.7.tgz -C ..
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