Apache Avro
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Categories: Data Engineering, Data Science | Tags: Avro, HDFS, Hive, ORC, Big Data, JSON, Parquet, Data Lake, File Format
Choosing an appropriate file format is essential, whether your data transits on the wire or is stored at rest. Each file format comes with its own advantages and disadvantages. We covered them in a…
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Faster model development with H2O AutoML and Flow
Categories: Data Science, Learning | Tags: Automation, Cloud, H2O, Machine Learning, MLOps, On-premises, Open source, Python
Building Machine Learning (ML) models is a time-consuming process. It requires expertise in statistics, ML algorithms, and programming. On top of that, it also requires the ability to translate a…
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Comparaison of different file formats in Big Data
Categories: Big Data, Data Engineering | Tags: Avro, HDFS, Hive, MapReduce, ORC, Batch processing, Big Data, Business intelligence, CSV, Data Analytics, Data structures, Database, JSON, Protocol Buffers, Hadoop, Kafka, Parquet, Spark, Kubernetes, XML
In data processing, there are different types of files formats to store your data sets. Each format has its own pros and cons depending upon the use cases and exists to serve one or several purposes…
By Aida NGOM
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Data Lake ingestion best practices
Categories: Big Data, Data Engineering | Tags: Avro, Hive, NiFi, ORC, Data Governance, HDF, Operation, Protocol Buffers, Spark, Data Lake, File Format, Registry, Schema
Creating a Data Lake requires rigor and experience. Here are some good practices around data ingestion both for batch and stream architectures that we recommend and implement with our customers…
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Options to connect and integrate Hadoop with Oracle
Categories: Data Engineering | Tags: Avro, HDFS, Hive, MapReduce, Sqoop, Database, Java, NoSQL, Oracle, R, RDBMS, SQL
I will list the different tools and libraries available to us developers in order to integrate Oracle and Hadoop. The Oracle SQL Connector for HDFS described below is covered in a follow up article…
By David WORMS
May 15, 2013