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copied!<p>Removing entire nodes (groups or datasets) from a hdf5 file should be no problem.<br> However if you want to reclaim the space you have to run the <code>h5repack</code> tool. </p> <p>From the <a href="http://www.hdfgroup.org/HDF5/doc/UG/UG_frame10Datasets.html">hdf5 docs</a>: </p> <blockquote> <p>5.5.2. Deleting a Dataset from a File and Reclaiming Space</p> <p>HDF5 does not at this time provide an easy mechanism to remove a dataset from a file or to reclaim the storage space occupied by a deleted object.</p> <p>Removing a dataset and reclaiming the space it used can be done with the H5Ldelete function and the h5repack utility program. With the H5Ldelete function, links to a dataset can be removed from the file structure. After all the links have been removed, the dataset becomes inaccessible to any application and is effectively removed from the file. The way to recover the space occupied by an unlinked dataset is to write all of the objects of the file into a new file. Any unlinked object is inaccessible to the application and will not be included in the new file. Writing objects to a new file can be done with a custom program or with the h5repack utility program.</p> </blockquote> <p>Alternatively you can also have a look into PyTables`s <a href="http://pytables.github.com/usersguide/utilities.html">ptrepack</a> tool. PyTables should be able to read h5py hdf5 files and the <code>ptrepack</code> tool is similar to the <code>h5repack</code>. </p> <p>If you want to remove records from a datasets, then you probably have to retrieve the records you want to keep and create a new dataset and remove the old one.<br> PyTables supports <a href="http://pytables.github.com/usersguide/libref.html#table-methods-writing">removing</a> rows, however it's not recommended. </p>

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