{"id":29556468,"url":"https://github.com/theveryhim/stream-data-analysis","last_synced_at":"2025-07-18T10:11:39.880Z","repository":{"id":302933076,"uuid":"1013970369","full_name":"theveryhim/Stream-data-analysis","owner":"theveryhim","description":"Filtering, sampling and analysis on a news data set using stream simulation.","archived":false,"fork":false,"pushed_at":"2025-07-04T20:12:18.000Z","size":31224,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-07-04T21:23:23.393Z","etag":null,"topics":["pyspark","stream-data-analysis","stream-processing"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Stream data analysis\n\n## *news_dataset_MDA2024*\n- Implementing a streaming data processing system using Structured Streaming in PySpark framework.\n- Process the input data entered into the system continuously and in real time (real-time) from a news source and extract useful information from it.\n- Filter the data flow based on different tasks\n```markdown\nTime: 2024-12-29 12:00:00\nCategory: PARENTING, Count: 1\nCategory: CULTURE \u0026 ARTS, Count: 1\nCategory: U.S. NEWS, Count: 5\nCategory: COMEDY, Count: 1\nCategory: WORLD NEWS, Count: 2\n\n------------------------------\nTime: 2024-12-29 12:00:20\nCategory: SPORTS, Count: 1\nCategory: CULTURE \u0026 ARTS, Count: 1\nCategory: U.S. NEWS, Count: 1\nCategory: WORLD NEWS, Count: 6\nCategory: TECH, Count: 1\n\n------------------------------\n...\n```\n\n## *web_streaming_dataset*:\n\n- Get acquainted with the important algorithms in the analysis of stream data and implement these algorithms(DGIM \u0026 FM) in PySpark framework\n- Estimate the number of 1 bits (successful user requests) in each window using the DGIM algorithm\n\u003cp align=\"center\"\u003e\n    \u003cimg src=\"1.png\" alt=\"Descriptive Alt Text\" class=\"fit-width-image\"\u003e\n\u003c/p\u003e\n\n- Using *FM* algorithm, estimate the number of unique users who have accessed the website.\n```markdown\nActual number of unique users: 1491\nEstimated number of unique users: 1575.3846153846155\n```\n\n## Persian Twitter Dataset(*dataset*)\n- Both task and implementation of this section is provided as *Task3*\n- Using PySpark's Structured Streaming, process new tweets in real-time and identify and count the hashtags of each tweet.\n```markdown\n+--------------------+--------------------+-------------+\n|              window|             hashtag|hashtag_count|\n+--------------------+--------------------+-------------+\n|{2023-12-01 06:14...|         پرستو_معینی|            1|\n|{2023-11-22 11:18...|        دلیران_میدان|            1|\n|{2023-12-01 06:14...|          زهرا_صفایی|            1|\n|{2023-11-10 07:10...|         درمان_سرطان|            1|\n|{2023-11-10 07:10...|       سرطان_پروستات|            1|\n...\n```\n- Use the sentiment feature of each tweet to analyze sentiment and calculate and display the average sentiment for each hashtag in real-time.\n```markdown\n+--------------------+-------------+\n|             hashtag|avg_sentiment|\n+--------------------+-------------+\n|          حسن_روحانی|          0.0|\n|         قیام_سراسری|          0.0|\n|                 یمن|          0.0|\n|       آرمیتا_گراوند|          0.0|\n|    KingRezaPahlavi‌|          0.0|\n...\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftheveryhim%2Fstream-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftheveryhim%2Fstream-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftheveryhim%2Fstream-data-analysis/lists"}