Questions tagged [bigdata]

Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis and visualization.

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2answers
39 views

Dimensionality reduction for millions of features

I have a dataset with 10 million observations and 1 million sparse features. I would like to build a binary classifier for predicting a particular feature of interest. My main problem is how to deal ...
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0answers
12 views

Repeating values caught with a binary classifier

If my machine is broken, it starts to repeat certain channels. Thing is if there are no out-liars, it is difficult to tell it's broken as we would expect all data points to be around the same value. I ...
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1answer
39 views

How do I normalize json data into pandas (Covid-19 data) [closed]

I am trying to import all up-to-date datasets in JSON format on the covid-19 pandemic into a pandas dataframe. I believe it should be possible by using ...
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1answer
25 views

Best way to preprocess data

I need to create a machine learning model to predict if a structure is an hotel or an apartment. I have a dataset structured as well: ...
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0answers
60 views

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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0answers
11 views

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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0answers
7 views

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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4answers
583 views

Best platform to work with when having millions of rows in dataframe

I have table with around 20 features and millions of observations (rows). I need to create model base on this table, however, as it is huge, training models like random forest or XGB takes forever. I'...
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1answer
36 views

Data Art/ Data Visualization Art/ Information Art

Few days ago, I learned about data art/ data visualization art/ information art. I think I have interest in it. I want to see how I can use my data science skills in this area. However, I don't know ...
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0answers
24 views

Word count with map reduce

Suppose we use an input file that contains the following lyrics from a famous song: We’re up all night till the sun We’re up all night to get some The input pairs for the Map phase will be the ...
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2answers
139 views

Where can I find study materials? [closed]

Can anyone recommend me some material (books, blogs, youtube channels, ...) to study statistics, Machine Learning and in general Data Science topics? Thanks
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1answer
24 views

How do I create a dataset from many CSV files that is too large for RAM

I have been handed about 40 GB of CSV files that I need to turn into a database. The files are arranged in a file structure that uses location in that file structure to create a relationship between ...
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11 views

Find a column by name in a row in scala spark

I have a Seq[Row].Each row is an Array of Struct.Struct has four fields: a,b,c and d all of which are String.The data in a particular row is something like this: [{"a":"ahahk",&...
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0answers
76 views

Best way to find nearest neighbor distance for large datasets

I am a grad student doing research using generative machine learning with pytorch, and I have generated a set of points. I would like to check how similar these new points are to the points I used in ...
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2answers
185 views

Fastest way to replace a value in a pandas DataFrame?

I am loading in 1.5m images with 80,000 classes (or I will have to when I eventually train) into a Keras generator and am using a pandas dataframe to do so. The problem is, with so many images, my ...
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1answer
57 views

How to do EDA on large datasets

I have a table in Postgres with ~5million records. When I load the dataset using pandas to perform EDA, I run out of memory. ...
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0answers
42 views

KMeans using Mapreduce in Python

I wrote a mapreduce code in python which works locally i.e., cat test_mapper |python mapper.py sort the result, and ...
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0answers
13 views

suggestion needed for big data development

I am trying to find out what is state of the art with database, python, and big data. My starting point began with a SQL server, and multiprocessing pandas, and dask. Imagine I need to maintain a ...
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3answers
142 views

Efficiently modify a large csv file in Pandas

I have a csv file and would like to do the following modification on it: ...
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0answers
245 views

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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1answer
42 views

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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1answer
22 views

How to choose feedforward architecture for few number of features but very large instance?

Assume I have 1 million of data instance and each instance contains 100 feature. For each instance, I also have a lable. The ...
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0answers
33 views

Examples of Open source huge business intelligence datasets

I've observed that many of the datasets available for traditional ML and data science algorithms seem to be in the order of MB. I assumed these may be because earlier computers were not that ...
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0answers
172 views

XGBoost incremental training for big datasets

I am trying to train an XGBoost model on a quite big dataset (tens of GB, almost a hundred). I have been trying to use some libraries such as Dask to deal with this problem, without any success due to ...
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0answers
13 views

What are the execution service and the event service in Netflix big data

From the following article by the netflix engineering team: The core architecture of the big data platform at Netflix involves three key services. These are the execution service (Genie), the ...
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1answer
246 views

How do you do 1-vs-rest classifiers in XGBoost Library (Not Sklearn)?

I am working with a very large dataset that would benefit from using training continuation with the xgb_model parameter in ...
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1answer
71 views

Subsampling the “right” amout of data to train an ML model

I am training a machine learning model (i.e., a classifier) on a large dataset. I know that I can get the same results using less data (about 30%) but I would like to avoid the trial and error process ...
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0answers
11 views

Scalable Infrence Server for Object Detection

I have created a Django service (nginx + Gunicorn) for object detection models. For my case i have 50+ models with resnet 50 based back bone. Server Machine Specification: 16 CPU 64 GB Ram I have ...
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0answers
27 views

What should be the architecture design for the dataset to be used for a machine learning API

I have aroud 30GB of market dataset in csv format which is downloaded onto my server computer everyday. Now I want to use this dataset to do some computations and provide some analysis. The user will ...
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0answers
40 views

How do you perform basic statistical analysis on a Binary Dataset?

I have never worked with a Binary dataset (1 and 0) (True or False) so I'm unsure what kind of statistical tests I should run to draw up simple conclusions. I'm doing a data science project and the ...
5
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2answers
155 views

What is the best way (cheapest / fastest option) to train an model on massive dataset (400GB+, 100m rows x 200 columns)?

I have a 400GB data set that I want to train a model on. What is the cheapest method to train this model? The options I can think of so far are: AWS instance with massive RAM and train CPU (slow, but ...
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0answers
67 views

Working with mySQL and pytorch Dataset

I am working with high frequency time indexed data. We have 2 types of data each with about 5 columns. For each type of data we have 2500 streams coming in and being updated every 1ms-100ms (the ...
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0answers
39 views

Extracting possible relationships and insights from a large dataset

I have a dataset with about 26'000 variables and 33'000 continuous observations. My task is to extract any interesting insights/possible relationships between various variables. I am looking for any ...
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0answers
17 views

How to Combine Oracle and Snowflake/Redshift data on the fly

Have a Schema.Table_Name on Oracle. Exactly similar table is on Snowflake with same metadata(Schema.Table_Name). How can I combine data from two on the fly without moving Oracle data to Redshift. Most ...
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1answer
20 views

Where can I find a dataset that contains criminal case sentencing data? [closed]

I would like to study a dataset where each record represents a criminals case in the US and contains attributes such as: Type of crime Defendant Age/Sex/Race Plea Verdict Sentence Is there a dataset ...
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0answers
33 views

In Spark, what's the role of each of Cluster manager and Spark Context?

What's the role of a cluster manager and the role spark context (Driver program) in terms of managing worker nodes. How do they communicate with each other (and with the worker nodes) and when they do ...
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0answers
17 views

Trigger job in SAP BW from SAC

Is there a way to have the following occur: When a job is finished on the SAC (SAP Analytics Cloud) side, a job on the SAP BW side should be triggered. Is that at all possible? I have found this which ...
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0answers
51 views

Difference between MapReduce, Dryag and Pregel in terms of efficiency

What is the difference between the three parallel processing paradigms: MapReduce, Dryag, and Pregel in terms of efficiency for big data analytics applications? Thank you.
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1answer
18 views

What data to collect to create useful insights?

I am creating a Social Media app and I want to know what type of data shall I collect to create useful insights for Business accounts or Content Creators? For example if I want to create an insight ...
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1answer
68 views

How to train a model using a daunting huge training dataset

I have an extremely huge dataset and I'm wondering me how could be the right way to set an experiment to use this data to train a model. I understand that I can use data-reduction to, for instance, ...
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0answers
38 views

How to Integrate/map Population Data with/over Sample Data

Problem Definition: Our organization is conducting different type of surveys and Census in our country. The basic difference between Census and Survey is that, the target of Census is the Complete ...
2
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0answers
53 views

Clustering large set of images

I've got some big datasets of images (a few million each), and I would like to cluster them according to images' visual similarities. I've extracted a feature vector for each image; the space of ...
2
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0answers
44 views

What is the difference between Pachyderm and Git?

I learned that tools like Pachyderm version-control data, but I cannot see any difference between that tool with Git. I learned from this post that: It holds all your data in a central accessible ...
3
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1answer
129 views

Why do machine learning engineers insist on training with more data than validation set?

Among my colleagues I have noticed a curious insistence on training with, say, 70% or 80% of data and validating on the remainder. The reason it is curious to me is the lack of any theoretical ...
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1answer
34 views

How to grade an interaction that a user had with a post with an AI based on big data?

Context I'm creating a social network. The thing is, I don't want to order posts by likes, or something like that, I'm using an AI (lightfm in ...
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1answer
32 views

How do data types influence hardware (CPU / GPU / TPU) performance?

I am currently dealing with a relatively big data set, for which I have some memory usage concerns. I am dealing with most of the different data types : floats, integers, Booleans, characters strings ...
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0answers
16 views

Ideas on handling large quantities of "waste" data

Hello and thank you for taking time out of your day to help me. I am currently working on developing a machine vision application for production monitoring. The application handles images, about 20,...
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1answer
898 views

How to store efficiently very large sparse 3D matrices

To train a CNN, I have stacked arrays of images over observations [observations x width x length]. The dataset is very sparse ($95\%$). What would be an efficient ...
2
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1answer
53 views

Size of datasets over years

I am looking for statistics, to understand the evolution of the size of the (public) dataset over the years. I just found the following statistics: The poll of KDnuggets that actually shows that over ...
2
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1answer
742 views

How does skewed data affect deep neural networks?

I'm playing around with deep neural networks for a regression problem. The dataset I have is skewed right and for a linear regression model, I would typically perform a log transform. Should I be ...

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