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data technology. it explains several tools and methodologies of performing operations on a large pool of data. the main focus of this section is to clarify the differences between the rivals to make it clear that which technology has to be used to meet different requirements. apache storm vs apache spark...
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: apache sparktm is a fast and general engine for large-scale data processing. spark uses apache arrow to improve performance of conversion between spark dataframe and pandas dataframe enable a set of vectorized user-defined functions (pandas_udf) in pyspark. dask : python library for parallel and distributed...
warehousing tasks such as extract/transform/load (etl), reporting, and data analysis. a mechanism to impose structure on a variety of data formats access to files stored either directly in apache hdfs tm or in other data storage systems such as apache hbase tm query execution via apache tez tm , apache spark...
warehousing tasks such as extract/transform/load (etl), reporting, and data analysis. a mechanism to impose structure on a variety of data formats access to files stored either directly in apache hdfs tm or in other data storage systems such as apache hbase tm query execution via apache tez tm , apache spark...
: apache sparktm is a fast and general engine for large-scale data processing. spark uses apache arrow to improve performance of conversion between spark dataframe and pandas dataframe enable a set of vectorized user-defined functions (pandas_udf) in pyspark. dask : python library for parallel and distributed...
warehousing tasks such as extract/transform/load (etl), reporting, and data analysis. a mechanism to impose structure on a variety of data formats access to files stored either directly in apache hdfs tm or in other data storage systems such as apache hbase tm query execution via apache tez tm , apache spark...
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