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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 usinggather. MATLAB automatically optimizes the queued calculations by minimizing the number of passes through the data. For more information, seeTall Arrays for Out-of-Memory Data.

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

Funktionen

alle erweitern

tall Create tall array
数据存储 Create datastore for large collections of data
gather Collect tall array into memory after executing queued operations
write Write tall array to local and remote locations for checkpointing
mapreducer Define execution environment for mapreduce or tall arrays
tallrng Control random number generation for tall arrays
istall Determine if input is tall array
classUnderlying Class of underlying data in tall array
isaUnderlying Determine if tall array data is of specified class
matlab.tall.transform Transform array by applying function handle to blocks of data
matlab.tall.reduce Reduce arrays by applying reduction algorithm to blocks of data
matlab.tall.movingWindow Apply moving window function to blocks of data
matlab.tall.blockMovingWindow Apply moving window function and block reduction to padded blocks of data

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