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Apache Spark review
Dunstan Matekenya
Data Scientist at a financial services firm with 10,001+ employees
Open-source solution for data processing with portability
Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly. While many choices now exist, Spark remains easy to use, particularly with Python. You can utilize familiar programming styles similar to Pandas in Python, including object-oriented programming. Another advantage is its...
Apache Spark review
Bharghava Raghavendra Beesa
Senior Developer at Infosys
Faster data transformations achieved but scheduling dependencies require external...
The Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, one task should trigger another based on completion, however, Spark can't manage these dependent loads. We focus on specific compute tasks that we...
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