Questions tagged [pyspark]

The Spark Python API (PySpark) exposes the apache-spark programming model to Python.

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Exploratory data analysis (EDA) on large dataset

I am working with lots of data (we have a table that produces 30 million rows daily). What is the best way to explore it (do on EDA)? Take a frictional slicing of the data randomly (100000 rows) or ...
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Does one-hot encode effects chi-square test?

I am doing a feature selection for a data science project with one of those feature being a high cardinality categorical variable (for context, it’s nationality). I know chi-square test could handle ...
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Contunious model update

Hello I have a trained model on credit card fraud detection, however I want to find a solution so I can update the model parameters with new input records to simulate the pattern changes, is there any ...
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Computing number of business days between start/end columns

I have two Dataframes facts: columns: data, start_date and end_date holidays: column: <...
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PySpark createDataFrame() throws segmentation fault on Mac

I'm trying to learn PySpark. Finally got it installed following the tutorial here: https://sparkbyexamples.com/pyspark/install-pyspark-in-anaconda-jupyter-notebook/ However, even though I am now able ...
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Is it possible to implement an rdd version of a for loop having map and reduce using pyspark?

I need to test an algorithm that computes a function on a dataframe where in each execution I drop a column and computes the function. This is a example in python pyspark but without using rdd: ...
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Group a spark dataframe by a starting event to an ending event

Given a series of events (with datetime) such as: failed, failed, passed, failed, passed, passed I want to retrieve the time from when it first "failed" to when it first "passed," ...
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Generalized Additive Modeling Apache Spark implementation

Does Spark MLlib support Generalized Additive Modeling? How does one go about implementing GAM models in Spark? I want to implement GAM (Generalized additive model) model in Spark. Based on my ...
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Feature engineering/selection within PySpark CrossValidator

Multiple sources I've read recently have argued that if using cross-validation to assist with model training/tuning, then aspects of the model development process such as feature selection should be ...
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Is model training using spark ML distributed?

Is model training using spark ML distributed? If training happens on a single machine then why use spark?
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CREATE TABLE USING Oracle DATA_SOURCE

I am trying to create a table using ORACLE as a data source using spark query but getting an error. %sql CREATE TABLE TEST USING org.apache.spark.sql.jdbc OPTIONS ( url "jdbc:oracle:thin:@...
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Pyspark vs Pandas: When should we consider to change from Pandas to Pyspark

We trained a model in a single server using pandas, dataframe = 2.000.000 rows(I run it later in my own laptop), now we are migrating the code to the cloud and in that case to Databricks. In ...
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Creating table in Databricks using the table from Oracle

I am trying to create a table in Databricks using a object in Oracle Db, but getting an error ...
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Best approach to find top-k most likely items

I am working with large datasets of papers and authors. I am trying to find top-k authors that are likely to cite a new paper on the unseen dataset (https://www.aminer.org/aminernetwork). My setup is ...
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Huge matrix multiplication with PySpark

I am currently struggling with a problem. I have been googling around and cannot find an answer. Also I am kinda new to PySpark and Spark maybe that's why I am struggling. Let's say I have a huge $m \...
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How to get dummy variables from "first name"

I intend to predict the age of customers using some features. There are some categorical features that I need to convert to dummy variables before the modelling stage. Since the datasets are so big (...
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Data Pipelines - Apache Spark - Updating Another Data Store or Input to Queue

What is the correct way to think about or approach something like Spark breaking down a 160GB file into smaller manageable parts, or single records and then doing something like updating records in ...
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How can improve the performance of clustering algorithm concerning similar/same records?

I want to check/experiment efficiency improvement of clustering algorithm under the title of Statistical preprocessing was done by including statistical frequency (counts) into dataframe concerning ...
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Spark Dataframe APIs vs Spark SQL

I have a relatively complex query which runs against a database and contains multiple join statements, lead/lag functions, subquery, etc. These tables are available as individual files in my object ...
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Is there a way to add custom (virtually all popular) metrics to BinaryClassificationEvaluator from pyspark MFlow library?

I am trying to make runs with mlflow from pyspark and I would like to obtain multiple metrics from that (not only ones suggested in the documentation which are areaUnderROC and areaUnderPR).
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Analysing process data with sub groupings and checking for correlation

I have a dataset of process data for different equipment with many sensors. I would like to check the correlation of the different sensors to see if there is any strong correlation between some ...
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How to implement predict_proba() with spark.ml logistic regression

In sklearn it is possible to use the predict_proba() function to obtain the probability matrix. Since in ...
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Access global variable from UDF (User Defined Function) in python in spark

I am trying to alter a global variable from inside a pyspark.sql.functions.udf function in python. But, the change in not getting reflected in the global variable. ...
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PySpark for Big Data and RAM usage

I'm trying to figure out the best and most efficient method of handing ETL operations for big data. My question is this. Say I have a table that is ~50 GB in size. In order to effectively transfer the ...
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Where and how to do large scale supervised machine learning?

I'm beginner in ML and I have a large dataset that has 15 features with 6M rows, so it becomes challenging to work on it locally. I can train one model locally but to perform hyper parameter tuning ...
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ML modeling a data with big amount of rows

I want to do ML modeling such XGboost, KNN, and similar models on data with 9 numerical features and more than 25 million rows and the size of data is almost 2.5 Gig and I prefer to use all the data ...
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Why do I need to create a dataframe just to add a column? [closed]

So I worked with a bit of pandas and in that, it's easy to add a column to an existing dataframe. But in spark, a new dataframe needs to be created using 'withColumn'. I'm a complete newbie so is ...
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Pyspark.read from MariaDB fetches duplicate header rows instead of data

It's a very strange issue- instead of fetching data like expected, it returns every row as a duplicate of the header. Every cell is a literal string of the column name. If I don't use the query like ...
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PySpark Crossvalidation error

I want to do a very simple cross validation using LogisticRegression. Here is my code: ...
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Spark: How to run PCA parallelized? Only one thread used

I use pySpark and set my configuration like following: ...
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multi-label prediction with pySpark

I am new to Spark I am using pyspark to predict a multi label results. I have converted multi labels to binary So my labels will look like this ...
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PicklingError in pyspark (PicklingError: Can't pickle <class '__main__.Person'>: attribute lookup Person on __main__ failed)

I am unable to pickle the below class. I am using data bricks 6.5 ML (includes Apache Spark 2.4.5, Scala 2.11) ...
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Creating more than one worker nodes for local windows machine [closed]

I am using windows laptop. And I installed apache spark for my laptop. And I try to measure spark performance by changing spark components. because of that I want to create more than one worker nodes ...
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Remove all columns where the entire column is null

I have a very dirty csv where there are several columns with only null values. I would like to remove them. I am trying to select all columns where the count of null values in the column is not equal ...
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How to run Spark python code in Jupyter Notebook via command prompt

I am trying to import a data frame into spark using Python's pyspark module. For this, I used Jupyter Notebook and executed the code shown in the screenshot below After that I want to run this in CMD ...
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cannot access hive from spark [closed]

I am trying to install a hadoop + spark + hive cluster. I am using hadoop 3.1.2, spark 2.4.5 (scala 2.11 prebuilt with user-provided hadoop) and hive 2.3.3 (also tried 3.1.2 with the exact same ...
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Spark/Databricks: GPU does not appear to be utilized for ML regression (cross-validation, prediction) notebook

I have created and attached a notebook to a GPU-enabled Databricks cluster (6.4 ML (includes Apache Spark 2.4.5, GPU, Scala 2.11), EC2 type: p2.xlarge). I have started running the notebook that ...
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Pyspark Dataframes to Pandas and ML Ops - Parallel Execution Hold?

If I convert a spark dataframe into a pandas dataframe and subsequently apply pandas operations and sklearn models to the dataset in databricks, will the operations from pandas and sklearn be ...
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3 answers
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Is there a cost associated with converting Koalas dataframe to Spark dataframe?

I know that pandas works "under the hood" with numpy arrays stored in dictionaries. In contrast, Koalas works with the underlying Spark framework. Does that mean that there is no extra cost associated ...
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PySpark: How do I specify dropna axis in PySpark transformation?

I would like to drop columns that contain all null values using dropna(). With Pandas you can do this with setting the keyword argument ...
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How to apply K-Medoids in PySpark?

the pyspark ml library does not provide any clustering methods for K-Medoids. So my question is, how can one apply K-Medoids in a pyspark context?
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Tool/Technology/Framework to process file with 1GB [closed]

I'm new to datascience, but I have the following problem: 1) Read a file of 1GB, which each line is a json object 2) There are two more files, much smaller, which I need to JOIN some data In this ...
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How to split a CSV into a dataframe without newline

Currently I'm using pyspark to make my df from a csv. However when I take the data in, it puts each element on a new line. Is there any way to keep the elements separate, and keep them on the same ...
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Feature importance using logistic regression in pyspark

I am using logistic regression in PySpark. I have after splitting train and test dataset ...
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Incremental modelling of kmeans in pyspark

I have a large dataset and trained the model with kmeans for the first time. I saved the model and pipeline used . Now again I started collecting data. After sufficient data is collected using old ...
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2 votes
1 answer
545 views

Calculating Rank Ordering Error Metric for implicit recommendation

I'm reading Collaborative Filtering for Implicit Feedback Datasets. On page 6 they detail their evaluation strategy, which they define as mean Expected Percentile Ranking with the following formula: $...
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How to select multiple columns in a RDD with Spark (pySpark)?

Lets say I have a RDD that has comma delimited data. Each comma delimited value represents the amount of hours slept in the day of a week. So for i.e. [8,7,6,7,8,8,5] How can I manipulate the RDD so ...
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customer segmentation with unbalanced data

I am trying to do a customer segmentation on my transactional data and I am struggling a little bit on the best approach. Since it is an unsupervised model I can throw it to any algorithm and get some ...
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Which ML method for multiclass (non-binary) text classification should I choose (from SparkML)?

I am working on a quite big dataset that will be processed on the cluster, so this is why I am using PySpark for that purpose. The presentable records of this dataset have a such structure: ...
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How to store subset of columns from a csv file?

I need to create a table in hive (or Impala) by reading from a csv file (named file.csv), ...
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