Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
APPLICATION OF PYTHON AND JAVA LIBRARIES IN BIG DATA TECHNOLOGIES |
| Συγγραφείς: |
Erkin o‘g‘li, Sherzod Jovliboyev, Khudoyberdi o‘g‘li, Rahmatilla Khudoyberdiyev |
| Πηγή: |
JOURNAL OF SCIENCE, RESEARCH AND TEACHING; Vol. 5 No. 2 (2026): JOURNAL OF SCIENCE, RESEARCH AND TEACHING; 23-27 ; 2181-4406 |
| Στοιχεία εκδότη: |
Innova Science |
| Έτος έκδοσης: |
2026 |
| Θεματικοί όροι: |
Big Data, Python, Java, Pandas, Dask, PySpark, Hadoop, Apache Spark |
| Περιγραφή: |
In recent years, Big Data technologies have become an important strategic tool in the processes of data storage, processing, and analysis. This article analyzes the role of the Python and Java programming languages within the Big Data ecosystem, as well as the application of their key libraries—Pandas, Dask, and PySpark for Python, and Hadoop, native Apache Spark, and Apache Flink for Java. The study compares the performance efficiency, resource consumption, and operational stability of PySpark and Java/Scala-based Spark using an ETL (Extract, Transform, Load) pipeline as a case study. The results of the article provide a scientific and practical basis for selecting a programming language in Big Data projects. |
| Τύπος εγγράφου: |
article in journal/newspaper |
| Περιγραφή αρχείου: |
application/pdf |
| Γλώσσα: |
English |
| Relation: |
https://jsrt.innovascience.uz/index.php/jsrt/article/view/1039/870; https://jsrt.innovascience.uz/index.php/jsrt/article/view/1039 |
| Διαθεσιμότητα: |
https://jsrt.innovascience.uz/index.php/jsrt/article/view/1039 |
| Αριθμός Καταχώρησης: |
edsbas.A7FF78F7 |
| Βάση Δεδομένων: |
BASE |