Catalog import argument documentation.

docs/catalogs/arguments.rst

@@ -3,9 +3,9 @@ Catalog Import Arguments
 
 This page discusses a few topics around setting up a catalog pipeline.
 
-At a minimum, you need to pass the reader arguments that include where to find the input files,
-the column names for RA, DEC and ID, and where to put the output files. A minimal arguments block
-will look something like:
+At a minimum, you need arguments that include where to find the input files,
+the column names for RA, and DEC, and where to put the output files. 
+A minimal arguments block will look something like:
 
 .. code-block:: python
 
@@ -19,16 +19,76 @@ will look something like:
         output_path="./output",
     )
 
-You only need to provide the ``file_reader`` argument if you are using a custom file reader
-or passing parameters to the file reader. For example you might use ``file_reader=CsvReader(separator="\s+")``
-to parse a whitespace separated file.
 
-More details on each of these parameters is provided below.
+More details on each of these parameters is provided in sections below.
 
-For a full list of the available arguments, see the API documentation for 
+For the curious, see the API documentation for 
 :py:class:`hipscat_import.catalog.arguments.ImportArguments`, and its superclass
 :py:class:`hipscat_import.runtime_arguments.RuntimeArguments`.
 
+Pipeline setup
+-------------------------------------------------------------------------------
+
+Dask
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+We will either use a user-provided dask ``Client``, or create a new one with
+arguments:
+
+``dask_tmp`` - ``str`` - directory for dask worker space. this should be local to
+the execution of the pipeline, for speed of reads and writes. For much more 
+information, see :doc:`temp_files`
+
+``dask_n_workers`` - ``int`` - number of workers for the dask client. Defaults to 1.
+
+``dask_threads_per_worker`` - ``int`` - number of threads per dask worker. Defaults to 1.
+
+If you find that you need additional parameters for your dask client (e.g are creating
+a SLURM worker pool), you can instead create your own dask client and pass along 
+to the pipeline, ignoring the above arguments. This would look like:
+
+.. code-block:: python
+
+    from dask.distributed import Client
+    from hipscat_import.pipeline import pipeline_with_client
+
+    args = ...
+    with Client('scheduler:port') as client:
+        pipeline_with_client(args, client)
+
+If you're running within a ``.py`` file, we recommend you use a ``main`` guard to
+potentially avoid some python threading issues with dask:
+
+.. code-block:: python
+
+    from hipscat_import.pipeline import pipeline
+
+    def import_pipeline():
+        args = ...
+        pipeline(args)
+
+    if __name__ == '__main__':
+        import_pipeline()
+
+Resuming
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The import pipeline has the potential to be a very long-running process, if 
+you're importing large amounts of data, or performing complex transformations
+on the data before writing.
+
+While the pipeline runs, we take notes of our progress so that the pipeline can
+be resumed at a later time, if the job is pre-empted or canceled for any reason.
+
+When instantiating a pipeline, you can use the ``resume`` flag to indicate that
+we can resume from an earlier execution of the pipeline.
+
+If any resume files are found, we will only proceed if you've set the ``resume=True``.
+Otherwise, the pipeline will terminate.
+
+To address this, go to the temp directory you've specified and remove any intermediate
+files created by the previous runs of the ``hipscat-import`` pipeline.
+
 Reading input files
 -------------------------------------------------------------------------------
 
@@ -61,14 +121,18 @@ How to read them?
 
 Specify an instance of ``InputReader`` for the ``file_reader`` parameter.
 
-see the API documentation for 
-:py:class:`hipscat_import.catalog.file_readers.InputReader`
-
 We use the ``InputReader`` class to read files in chunks and pass the chunks
 along to the map/reduce stages. We've provided reference implementations for 
 reading CSV, FITS, and Parquet input files, but you can subclass the reader 
 type to suit whatever input files you've got.
 
+You only need to provide the ``file_reader`` argument if you are using a custom file reader
+or passing parameters to the file reader. For example you might use ``file_reader=CsvReader(separator="\s+")``
+to parse a whitespace separated file.
+
+You can find the full API documentation for 
+:py:class:`hipscat_import.catalog.file_readers.InputReader`
+
 .. code-block:: python
 
     class StarrReader(InputReader):
@@ -102,6 +166,9 @@ type to suit whatever input files you've got.
 
     )
 
+If you're reading from cloud storage, or otherwise have some filesystem credential
+dict, put those in ``input_storage_options``.
+
 Which fields?
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
@@ -111,13 +178,13 @@ There are two fields that we require in order to make a valid hipscatted
 catalog, the right ascension and declination. At this time, this is the only 
 supported system for celestial coordinates.
 
+If you're importing data that has previously been hipscatted, you may use
+``use_hipscat_index = True``. This will use that previously compused hipscat spatial
+index as the position, instead of ra/dec.
 
 Healpix order and thresholds
 -------------------------------------------------------------------------------
 
-Details for ``pixel_threshold``, ``highest_healpix_order``, and
-``constant_healpix_order`` arguments
-
 When creating a new catalog through the hipscat-import process, we try to 
 create partitions with approximately the same number of rows per partition. 
 This isn't perfect, because the sky is uneven, but we still try to create 
@@ -133,6 +200,8 @@ should adjust your parameters.
 For more discussion of the ``pixel_threshold`` argument and a strategy for setting
 this parameter, see notebook :doc:`/notebooks/estimate_pixel_threshold`
 
+For more discussion of the "Binning" and all other stages, see :doc:`temp_files`
+
 Alternatively, you can use the ``constant_healpix_order`` argument. This will 
 **ignore** both of the ``pixel_threshold`` and ``highest_healpix_order`` arguments
 and the catalog will be partitioned by healpix pixels at the
@@ -164,20 +233,70 @@ for either pipeline success or failure.
 Output
 -------------------------------------------------------------------------------
 
+Where?
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
 You must specify a name for the catalog, using ``output_artifact_name``.
 
 You must specify where you want your catalog data to be written, using
 ``output_path``. This path should be the base directory for your catalogs, as 
 the full path for the catalog will take the form of ``output_path/output_artifact_name``.
 
 If there is already catalog data in the indicated directory, you can force a 
-new catalog to be written in the directory with the ``overwrite`` flag. 
+new catalog to be written in the directory with the ``overwrite`` flag. It's
+preferable to delete any existing contents, however, as this may cause 
+unexpected side effects.
+
+If you're writing to cloud storage, or otherwise have some filesystem credential
+dict, put those in ``output_storage_options``.
+
+In addition, you can specify directories to use for various intermediate files:
+
+- dask worker space (``dask_tmp``)
+- sharded parquet files (``tmp_dir``)
+- intermediate resume files (``resume_tmp``)
+
+Most users are going to be ok with simply setting the ``tmp_dir`` for all intermediate
+file use. For more information on these parameters, when you would use each, 
+and demonstrations of temporary file use see :doc:`temp_files`
+
+How?
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+You may want to tweak parameters of the final catalog output, and we have helper 
+arguments for a few of those.
+
+``add_hipscat_index`` - ``bool`` - whether or not to add the hipscat spatial index
+as a column in the resulting catalog. The ``_hipscat_index`` field is designed to make many 
+dask operations more performant, but if you do not intend to publish your dataset
+and do not intend to use dask, then you can suppress generation of this column to
+save a little space in your final disk usage.
+
+The ``_hipscat_index`` uses a high healpix order and a uniqueness counter to create
+values that can order all points in the sky, according to a nested healpix scheme.
+
+``sort_columns`` - ``str`` - column for survey identifier, or other sortable column. 
+If sorting by multiple columns, they should be comma-separated. 
+If ``add_hipscat_index=True``, this sorting will be used to resolve the 
+index counter within the same higher-order pixel space.
+
+``use_schema_file`` - ``str`` - path to a parquet file with schema metadata. 
+This will be used for column metadata when writing the files, if specified.
+For more information on why you would want this file and how to generate it,
+check out our notebook :doc:`/notebooks/unequal_schema`.
+
+``debug_stats_only`` - ``bool`` - If ``True``, we will not create the leaf
+parquet files with the catalog data, and will only generate root-level metadata
+files representing the full statistics of the final catalog. This can be useful
+when probing the import process for effectiveness on processing a target dataset.
+
+``epoch`` - ``str`` - astronomical epoch for the data. defaults to ``"J2000"``
+
+``catalog_type`` - ``"object"`` or ``"source"``. Indicates the level of catalog data,
+using the LSST nomenclature:
 
-In addition, you can specify a directory to use for intermediate files, using
-``tmp_dir``, as well as a directory for dask to use for intermediate files using
-``dask_tmp``. This can be useful if you have additional scratch storage, or want
-to use local storage for intermediate files and remote storage for the final 
-catalog files.
+- object - things in the sky (e.g. stars, galaxies)
+- source - detections of things in the sky at some point in time.
 
-For more information on these parameters, when you would use each, and demonstrations 
-of temporary file use see :doc:`temp_files`
+Some data providers split detection-level data into a separate catalog, to make object
+catalogs smaller, and reflects a relational data model.

docs/index.rst

@@ -65,9 +65,6 @@ threading issues with dask:
    :caption: Catalogs
 
    catalogs/arguments
-   catalogs/resume
-   catalogs/debug
-   catalogs/advanced
    catalogs/temp_files
    catalogs/public/index