Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Statistical Analysis: Overview01:11

Statistical Analysis: Overview

16.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
16.7K
Data Collection by Observations01:08

Data Collection by Observations

15.4K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
15.4K
Data Reporting and Recording01:24

Data Reporting and Recording

5.6K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.6K
Dimensional Analysis02:19

Dimensional Analysis

25.2K
The concept of dimension is important because every mathematical equation linking physical quantities must be dimensionally consistent, implying that mathematical equations must meet the following two rules. The first rule is that, in an equation, the expressions on each side of the equal sign must have the same dimensions. This is fairly intuitive since we can only add or subtract quantities of the same type (dimension). The second rule states that, in an equation, the arguments of any of the...
25.2K
Dimensional Analysis01:23

Dimensional Analysis

2.3K
Dimensional analysis is a powerful tool that is used in physics and engineering to understand and predict the behavior of physical systems. The basic idea behind dimensional analysis is to express physical quantities in terms of fundamental dimensions such as the mass, length, and time. Derived dimensions like the velocity, acceleration, and force are derived from the combinations of these fundamental dimensions.
Dimensional analysis allows us to analyze and compare physical quantities on a...
2.3K
Dimensional Analysis03:40

Dimensional Analysis

66.7K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
66.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating the potential of acupuncture for Alzheimer's disease treatment: A meta-analysis and systematic review of mouse model studies.

Translational psychiatry·2026
Same author

Isokinetic Strength Recovery and Fear of Re-Injury After ACL Reconstruction in Male Soccer Players: A Retrospective Cohort Study.

Journal of clinical medicine·2026
Same author

Machine-Learning-Guided Chemical Metathesis for In Situ Construction of High-Entropy Alloy Interphases in Li-Metal Batteries.

ACS nano·2026
Same author

Anemoside B4 attenuates intestinal damage in chickens infected with Eimeria tenella: Mechanisms involving antioxidant defense, immune modulation, and barrier repair.

Poultry science·2026
Same author

Inhibitory effect of Cnidium monnieri aqueous extract on Eimeria tenella infection in chicks.

Poultry science·2025
Same author

Sophora flavescens Aqueous Extract Suppresses Eimeria tenella-Induced Inflammatory Responses and Regulates MAPK Pathway.

Poultry science·2025
Same journal

Structural Generalizability: The Case of Similarity Search.

Proceedings. ACM-SIGMOD International Conference on Management of Data·2026
Same journal

Flexible and Feasible Support Measures for Mining Frequent Patterns in Large Labeled Graphs.

Proceedings. ACM-SIGMOD International Conference on Management of Data·2024
Same journal

iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks.

Proceedings. ACM-SIGMOD International Conference on Management of Data·2021
Same journal

Optimal Join Algorithms Meet Top-<i>k</i>.

Proceedings. ACM-SIGMOD International Conference on Management of Data·2021
Same journal

Near-Optimal Distributed Band-Joins through Recursive Partitioning.

Proceedings. ACM-SIGMOD International Conference on Management of Data·2021
Same journal

Finding Related Tables in Data Lakes for Interactive Data Science.

Proceedings. ACM-SIGMOD International Conference on Management of Data·2020
See all related articles

Related Experiment Video

Updated: Feb 28, 2026

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

425

Big Data Analytics with Datalog Queries on Spark.

Alexander Shkapsky1, Mohan Yang1, Matteo Interlandi1

  • 1University of California, Los Angeles.

Proceedings. ACM-SIGMOD International Conference on Management of Data
|June 20, 2017
PubMed
Summary
This summary is machine-generated.

BigDatalog offers a declarative approach to complex analytics on Apache Spark, enhancing machine learning and graph processing. This system efficiently supports recursion, outperforming other large-scale Datalog systems.

Keywords:
DatalogMonotonic AggregatesRecursive QueriesSpark

More Related Videos

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.8K
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.3K

Related Experiment Videos

Last Updated: Feb 28, 2026

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

425
Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.8K
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.3K

Area of Science:

  • Cloud computing
  • Large-scale analytics
  • Machine learning
  • Graph analytics

Background:

  • Apache Spark is a popular platform for large-scale analytics, machine learning, and graph analytics.
  • Developing complex analytics in Spark requires expertise in algorithms and Spark's APIs.
  • Existing systems may lack efficient support for complex, recursive queries.

Purpose of the Study:

  • To propose BigDatalog, a system for concise declarative specification of complex queries in Spark.
  • To develop compilation and optimization techniques for efficient recursion support in Spark.
  • To evaluate BigDatalog's performance against state-of-the-art Datalog systems.

Main Methods:

  • Developed BigDatalog for declarative query specification.
  • Implemented compilation and optimization techniques for recursive queries in Spark.
  • Conducted experimental comparisons with other large-scale Datalog systems.

Main Results:

  • BigDatalog provides concise declarative specifications for complex analytics.
  • The proposed techniques enable efficient support for recursion in Spark.
  • Experimental results demonstrate the efficacy of BigDatalog and Spark for Datalog-based analytics.

Conclusions:

  • BigDatalog effectively addresses the challenge of complex analytics in Spark.
  • The system's declarative nature simplifies query development.
  • Spark is a viable and effective platform for advanced Datalog-based analytical tasks.