To make your data lake actionable for applications like personalization, artificial intelligence, machine learning, business analytics, business intelligence, Data Intelligence, etc, and to effectively manage petabytes of data volume in a single data lake table of Apache Hudi table format, the best approach is to store the data in various partition so that you can utilize it efficiently whenever needed.
At a high level, Hudi organizes data into a directory structure under the base path (root directory for the Hudi table). The directory structure can be flat (non-partitioned) or based on coarse-grained partitioning values set for the table.
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