What is the block size in HDF5?

Question

Quoting from the HDF5 Hyperslab doc -:

The block array determines the size of the element block selected from the dataspace.

The example shows in a 2x2 dataset having the parameters set to the following-:

start offset is specified as [1,1], stride is [4,4], count is [3,7], and block is [2,2]

will result in 21 2x2 blocks. Where the selections will be (1,1), (5,1), (9,1), (1,5), (5,5) I can understand that because the starting point is (1,1) the selection starts at that point, also since the stride is (4,4) it moves 4 in each dimension, and the count is (3,7) it increments 3 times 4 in direction X and 7 times 4 in direction Y ie. in its corresponding dimension.

But what I don't understand is what is block size doing ? Does it mean that I will get 21 2x2 dimensional blocks ? That means each block contains 4 elements, but the count is already set in 3 in 1 dimension so how will that be possible ?

Answer 1

A hyperslab selection created through H5Sselect_hypserslab() lets you create a region defined by a repeating block of elements.

This is described in section 7.4.2.2 of the HDF5 users guide found here (scroll down a bit to 7.4.2.2). The H5Sselect_hyperslab() reference manual entry might also be helpful.

Here is a diagram from the UG:

And here are the values used in that figure:

• offset = (0,1)
• stride = (4,3)
• count = (2,4)
• block = (3,2)

Notice how the repeating unit is a 3x2 element block. So yes, you will get 21 2x2 blocks in your case. There will be a grid of three blocks in one dimension and seven in the other, each spaced 4 elements apart in each direction. The first block will be offset by 1,1.

The most confusing thing about this API call is that three of the parameters have elements as their units, while count has blocks as its unit.

Edit: Perhaps this will make how block and count are used more obvious...