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Tall Arrays

Arrays with more rows than fit in memory

Tall arrays provide a way to work with data backed by a datastore that can have millions or billions of rows. You can create tall numeric arrays, cell arrays, categoricals, strings, datetimes, durations, or calendar durations, and you can use any of these tall types as variables in a tall table or tall timetable. Many operations and functions work the same way with tall arrays as they do with in-memory MATLAB® arrays, but most results are evaluated only when you request them explicitly using gather. MATLAB automatically optimizes the queued calculations by minimizing the number of passes through the data. For more information, see Tall Arrays for Out-of-Memory Data.

For more information about integrating with big data systems or compiling tall array algorithms, see Extend Tall Arrays with Other Products.


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tallCreate tall array
datastoreCreate datastore for large collections of data
gatherCollect tall array into memory after executing queued operations
writeWrite tall array to local and remote locations for checkpointing
mapreducerDefine execution environment for mapreduce or tall arrays
tallrngControl random number generation for tall arrays
istallDetermine if input is tall array
classUnderlyingClass of underlying data in tall array
isaUnderlyingDetermine if tall array data is of specified class
matlab.tall.transformTransform array by applying function handle to blocks of data
matlab.tall.reduceReduce arrays by applying reduction algorithm to blocks of data
matlab.tall.movingWindowApply moving window function to blocks of data
matlab.tall.blockMovingWindowApply moving window function and block reduction to padded blocks of data


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