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APPLICATION OF PYTHON AND JAVA LIBRARIES IN BIG DATA TECHNOLOGIES

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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
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  – Url: https://jsrt.innovascience.uz/index.php/jsrt/article/view/1039#
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  Data: APPLICATION OF PYTHON AND JAVA LIBRARIES IN BIG DATA TECHNOLOGIES
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  Data: <searchLink fieldCode="AR" term="%22Erkin+o‘g‘li%2C+Sherzod+Jovliboyev%22">Erkin o‘g‘li, Sherzod Jovliboyev</searchLink><br /><searchLink fieldCode="AR" term="%22Khudoyberdi+o‘g‘li%2C+Rahmatilla+Khudoyberdiyev%22">Khudoyberdi o‘g‘li, Rahmatilla Khudoyberdiyev</searchLink>
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  Data: JOURNAL OF SCIENCE, RESEARCH AND TEACHING; Vol. 5 No. 2 (2026): JOURNAL OF SCIENCE, RESEARCH AND TEACHING; 23-27 ; 2181-4406
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  Data: Innova Science
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  Data: 2026
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  Data: <searchLink fieldCode="DE" term="%22Big+Data%22">Big Data</searchLink><br /><searchLink fieldCode="DE" term="%22Python%22">Python</searchLink><br /><searchLink fieldCode="DE" term="%22Java%22">Java</searchLink><br /><searchLink fieldCode="DE" term="%22Pandas%22">Pandas</searchLink><br /><searchLink fieldCode="DE" term="%22Dask%22">Dask</searchLink><br /><searchLink fieldCode="DE" term="%22PySpark%22">PySpark</searchLink><br /><searchLink fieldCode="DE" term="%22Hadoop%22">Hadoop</searchLink><br /><searchLink fieldCode="DE" term="%22Apache+Spark%22">Apache Spark</searchLink>
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  Data: 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.
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  Data: https://jsrt.innovascience.uz/index.php/jsrt/article/view/1039/870; https://jsrt.innovascience.uz/index.php/jsrt/article/view/1039
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      – SubjectFull: Java
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