An IoT platform stores sensor data in a single large table containing 90 days of readings. Most queries filter on a specific date range (such as retrieving data from the last 24 hours). A database administrator proposes partitioning the table by day, creating 90 separate daily segments. How does this reduce query energy for date-filtered queries?

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Accepted Answer

Partitioning allows the database to skip entire segments whose date range does not match the query filter, reading only the relevant partition

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Partitioning compresses the data, reducing the total storage size

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Partitioning moves older data to slower storage, freeing faster storage for recent queries

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Partitioning creates an automatic index on the date column, speeding up all queries

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An IoT platform stores sensor data in a single large table containing 90 days of...

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