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Read large collections of data

The datastore function creates a datastore, which is a repository for collections of data that are too large to fit in memory. A datastore allows you to read and process data stored in multiple files on a disk, a remote location, or a database as a single entity. If the data is too large to fit in memory, you can manage the incremental import of data, create a tall array to work with the data, or use the datastore as an input to mapreduce for further processing. For more information, see Getting Started with Datastore.


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datastoreCreate datastore for large collections of data
tabularTextDatastoreDatastore for tabular text files
spreadsheetDatastoreDatastore for spreadsheet files
imageDatastoreDatastore for image data
parquetDatastoreDatastore for collection of Parquet files (depuis R2019a)
fileDatastoreDatastore with custom file reader
arrayDatastoreDatastore for in-memory data (depuis R2020b)
readRead data in datastore
readallRead all data in datastore
previewPreview subset of data in datastore
hasdataDetermine if data is available to read
resetReset datastore to initial state
writeallWrite datastore to files (depuis R2020a)
subsetCreate subset of datastore or FileSet (depuis R2019a)
isSubsettableDetermine whether datastore is subsettable (depuis R2022b)
shuffleShuffle all data in datastore
isShuffleableDetermine whether datastore is shuffleable (depuis R2020a)
numpartitionsNumber of datastore partitions
partitionPartition a datastore
isPartitionableDetermine whether datastore is partitionable (depuis R2020a)


combineCombine data from multiple datastores (depuis R2019a)
transformTransform datastore (depuis R2019a)


CombinedDatastoreDatastore to combine data read from multiple underlying datastores (depuis R2019a)
SequentialDatastoreSequentially read data from multiple underlying datastores (depuis R2022b)
TransformedDatastoreDatastore to transform underlying datastore (depuis R2019a)
KeyValueDatastoreDatastore for key-value pair data for use with mapreduce
TallDatastoreDatastore for checkpointing tall arrays


développer tout Base datastore class parallelization support to datastore subset and fine-grained parallelization support to datastore (depuis R2022b) Add Hadoop support to datastore (depuis R2019a) shuffling support to datastore File-set object for collection of files in datastore File-reader object for files in a datastore file writing support to datastore (depuis R2020a) Folder property support to datastore (depuis R2020a) File-set for collection of files in datastore (depuis R2020a) Blocked file-set for collection of blocks within file (depuis R2020a)