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CLUSTER BY only influences how future data is organized, it is not a precondition for partition creation.",{"id":125,"topic":9,"difficulty":126,"body":127,"options":128,"correct_key":118,"explanation":137},"01a00fd5-7da0-7bdf-921c-42509cddbaa3",2,"What is the approximate target size of a single Snowflake micro-partition, measured as uncompressed data?",[129,131,133,135],{"key":112,"text":130},"Between 1 MB and 8 MB of uncompressed data",{"key":115,"text":132},"Between 1 GB and 5 GB of uncompressed data",{"key":118,"text":134},"Between 50 MB and 500 MB of uncompressed data",{"key":121,"text":136},"Exactly 128 MB of uncompressed data, a fixed value","Snowflake targets micro-partitions containing between 50 MB and 500 MB of uncompressed data; the value actually stored on disk is smaller because Snowflake compresses the data. It is a target range, not a single fixed size.",{"id":139,"topic":9,"difficulty":126,"body":140,"options":141,"correct_key":112,"explanation":150},"01a00fd5-7da1-7f1f-8dd5-d9707b412f16","A row inside an existing Snowflake micro-partition needs to be updated by an UPDATE statement. What actually happens at the storage layer?",[142,144,146,148],{"key":112,"text":143},"Snowflake writes a new micro-partition with the changed data; the original is left unmodified",{"key":115,"text":145},"Snowflake locates the exact byte offset of the row and overwrites it in the existing micro-partition",{"key":118,"text":147},"Snowflake appends the changed row to the end of the same micro-partition file",{"key":121,"text":149},"Snowflake locks the micro-partition and rewrites only the affected column values","Micro-partitions are immutable. An UPDATE never modifies an existing micro-partition in place; Snowflake produces new micro-partitions holding the post-update state and the old micro-partition is superseded.",{"id":152,"topic":9,"difficulty":108,"body":153,"options":154,"correct_key":121,"explanation":163},"01a00fd5-7da4-7008-833c-df5066c2202e","Snowflake stores column data within a micro-partition in columnar form. What is the direct benefit of this for query scanning?",[155,157,159,161],{"key":112,"text":156},"It guarantees that every query touches the same number of bytes regardless of columns selected",{"key":115,"text":158},"It removes the need for Snowflake to keep any statistics about the data",{"key":118,"text":160},"It forces every query to read all columns of a table together as one unit",{"key":121,"text":162},"A query only needs to scan the columns it actually references, not the whole row","Because each column is stored independently inside a micro-partition, Snowflake can scan only the columns referenced by a query instead of reading entire rows, cutting down the bytes scanned.",{"id":165,"topic":9,"difficulty":126,"body":166,"options":167,"correct_key":118,"explanation":176},"01a00fd5-7da5-7de7-8e61-919c9df32d88","Which of the following is part of the metadata that Snowflake automatically maintains for each micro-partition?",[168,170,172,174],{"key":112,"text":169},"A full row-level checksum used to validate query results at runtime",{"key":115,"text":171},"The exact physical disk sector where the micro-partition is stored",{"key":118,"text":173},"The range of values (min\u002Fmax) and the number of distinct values for each column",{"key":121,"text":175},"A copy of every SQL statement that has ever touched that micro-partition","For each micro-partition, Snowflake stores metadata including the range of values for each column and the number of distinct values, among other properties used for query optimization.",{"id":178,"topic":9,"difficulty":108,"body":179,"options":180,"correct_key":112,"explanation":189},"01a00fd5-7da7-7574-b293-4d4dceaba9a9","What does 'pruning' mean in the context of Snowflake micro-partitions?",[181,183,185,187],{"key":112,"text":182},"Using stored metadata to skip micro-partitions that cannot match the query",{"key":115,"text":184},"Physically deleting old micro-partitions that are no longer needed for Time 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