diff --git a/tutorial/part3/chunking_introduction.ipynb b/tutorial/part3/chunking_introduction.ipynb index ce0c755..5e283d1 100755 --- a/tutorial/part3/chunking_introduction.ipynb +++ b/tutorial/part3/chunking_introduction.ipynb @@ -187,15 +187,15 @@ "__Chunking__ is splitting a dataset into small pieces. \n", "\n", "Original dataset, in one piece, \n", - "\n", + "\n", "\n", "and we split it into several smaller pieces. \n", - "\n", + "\n", "\n", "We split it into pieces so that we can process our data block by block or __chunk__ by __chunk__.\n", "\n", "In our case, for the moment, we used stackstac without specifying 'chunk' explicitly. The dataset is composed of 8MiB each, each contains, 1 time step, 1 band, 1024 x 1024 on x and y direction. \n", - "\n", + "\n", "\n", "\n", "If we have too small chunk size, we will divide our work flow in too small pieces, which can create too many communications, too many 'distirbution' overheads. \n", diff --git a/tutorial/part3/scaling_dask.ipynb b/tutorial/part3/scaling_dask.ipynb index f9943d0..0ffbfb2 100755 --- a/tutorial/part3/scaling_dask.ipynb +++ b/tutorial/part3/scaling_dask.ipynb @@ -272,11 +272,11 @@ "you will just need too look at the html link you have for your jupyterlab, and Dask dashboard port number, as highlighted in the figure below.\n", "\n", "\n", - "\n", - "\n", + "\n", + "\n", "\n", "Then click the orange icon indicated in the above figure, and type 'your' dashboard link (normally, you just need to replace 'todaka' to 'your username'). \n", - "\n", + "\n", "\n", "\n", "\n", @@ -285,7 +285,7 @@ "You can click several buttons indicated with blue arrows in above figures, then drag and drop to place them as your convenience. \n", "\n", "\n", - "\n", + "\n", "\n", "\n", "It's really helpfull to understand your computation and how it is distributed."