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The NetCDF NCZarr Implementation {#nczarr_head}

NCZarr Introduction {#nczarr_introduction}

Beginning with netCDF version 4.8.0, the Unidata NetCDF group
has extended the netcdf-c library to provide access to cloud
storage (e.g. Amazon S3
[1]
) by providing a mapping from a subset of the full netCDF Enhanced
(aka netCDF-4) data model to a variant of the Zarr
[4]
data model that already has mappings to
key-value pair cloud storage systems.
The NetCDF version of this storage format is called NCZarr
[2].

The NCZarr Data Model {#nczarr_data_model}

NCZarr uses a data model [2] that is,
by design, similar to, but not identical with the Zarr Version 2
Specification [4]. Briefly, the data
model supported by NCZarr is netcdf-4 minus the user-defined
types and the String type. As with netcdf-4 it supports
chunking. Eventually it will also support filters in a manner
similar to the way filters are supported in netcdf-4.

Specifically, the model supports the following.

  • "Atomic" types: char, byte, ubyte, short, ushort, int, uint, int64, uint64.
  • Shared (named) dimensions
  • Attributes with specified types – both global and per-variable
  • Chunking
  • Fill values
  • Groups
  • N-Dimensional variables
  • Per-variable endianness (big or little)

With respect to full netCDF-4, the following concepts are
currently unsupported.

  • String type
  • User-defined types (enum, opaque, VLEN, and Compound)
  • Unlimited dimensions

Enabling NCZarr Support {#nczarr_enable}

NCZarr support is enabled if the –enable-nczarr option
is used with './configure'. If NCZarr support is enabled, then
a usable version of libcurl must be specified
using the LDFLAGS environment variable (similar to the way
that the HDF5 libraries are referenced).
Refer to the installation manual for details.
NCZarr support can be disabled using the –disable-dap.

Accessing Data Using the NCZarr Prototocol {#nczarr_accessing_data}

In order to access a NCZarr data source through the netCDF API, the
file name normally used is replaced with a URL with a specific
format.

URL Format

The URL is the usual scheme:://host:port/path?query#fragment format.
There are some details that are important.

  • Scheme: this should be https or s3,or file.
    The s3 scheme is equivalent
    to "https" plus setting "mode=nczarr" (see below).
    Specifying "file" is mostly used for testing.
  • Host: Amazon S3 defines two forms: Virtual and Path.
    • Virtual: the host includes the bucket name as in
      bucket.s3.<region>.amazonaws.com
    • Path: the host does not include the bucket name, but
      rather the bucket name is the first segment of the path.
      For example s3.<region>.amazonaws.com/bucket
    • Other: It is possible to use other non-Amazon cloud storage, but
      that is cloud library dependent.
  • Query: currently not used.
  • Fragment: the fragment is of the form key=value&key=value&….
    Depending on the key, the =value part may be left out and some
    default value will be used.

Client Parameters

The fragment part of a URL is used to specify information
that is interpreted to specify what data format is to be used,
as well as additional controls for that data format.
For NCZarr support, the following key=value pairs are allowd.

  • mode=nczarr|zarr|s3|nz4|nzf… – The mode key specifies
    the particular format to be used by the netcdf-c library for
    interpreting the dataset specified by the URL. Using mode=nczarr
    causes the URL to be interpreted as a reference to a dataset
    that is stored in NCZarr format. The modes s3, nz4, and nzf
    tell the library what storage driver to use. The s3 is default]
    and indicates using Amazon S3 or some equivalent. The other two,
    nz4 and nzf are again for testing. The zarr mode tells the
    library to use NCZarr, but to restrict its operation to operate on
    pure Zarr Version 2 datasets.
  • log=<output-stream>: this control turns on logging output,
    which is useful for debugging and testing. If just log is used
    then it is equivalent to log=stderr.

NCZarr Map Implementation {#nczarr_mapimpl}

Internally, the nczarr implementation has a map abstraction
that allows different storage formats to be used.
This is closely patterned on the same approach used in
the Python Zarr implementation, which relies on the Python
MutableMap
[3] class.
In NCZarr, the corresponding type is called zmap.

The primary zmap implementation is s3 (i.e. mode=nczarr,s3) and indicates
that the Amazon S3 cloud storage is to be used. Other storage formats
use a structured NetCDF-4 file format (mode=nczarr,nz4), or a
directory tree (mode=nczarr,nzf)
The latter two are used mostly for debugging and testing.
However, the nzf format is important because it is intended
to match a corresponding storage format used by the Python
Zarr implementation. Hence it should serve to provide
interoperability between NCZarr and the Python Zarr.

NCZarr versus Pure Zarr. {#nczarr_purezarr}

The NCZARR format extends the pure Zarr format by adding
extra objects such as .nczarr and .ncvar. It is possible
to suppress the use of these extensions so that the netcdf
library can read and write a pure zarr formatted file.
This is controlled by using mode=nczarr,zarr combination.

Notes on Debugging NCZarr Access {#nczarr_debug}

The NCZarr support has a logging facility.
Turning on this logging can
sometimes give important information. Logging can be enabled by
using the client parameter "log" or "log=filename",or by
setting the environment variable NCLOGGING.
The first case will send log output to standard error and the
second will send log output to the specified file. The environment
variable is equivalent to log.

Amazon S3 Storage {#nczarr_debug}

The Amazon AWS S3 storage driver currently uses the Amazon
AWS S3 Software Development Kit for C++ (aws-s3-sdk-cpp).
In order to use it, the client must provide some configuration
information. Specifically, the ~/.aws/config file should
contain something like this.

[default]
output = json
aws_access_key_id=XXXX...
aws_secret_access_key=YYYY...

Addressing Style

The notion of "addressing style" may need some expansion.
Amazon S3 accepts two forms for specifying the endpoint
for accessing the data.

  1. Virtual – the virtual addressing style places the bucket in
    the host part of a URL. For example:
https://<bucketname>.s2.<region>.amazonaws.com/
  1. Path – the path addressing style places the bucket in
    at the front of the path part of a URL. For example:
https://s2.<region>.amazonaws.com/<bucketname>/

The NCZarr code will accept either form, although internally,
it is standardized on path style.

Zarr vs NCZarr {#nczarr_vs_zarr}

Data Model

The NCZarr storage format is almost identical to that of
the the standard Zarr version 2 format.
The data model differs as follows.

  1. Zarr supports filters – NCZarr as yet does not
  2. Zarr only supports anonymous dimensions – NCZarr supports
    only shared (named) dimensions.
  3. Zarr attributes are untyped – or perhaps more correctly
    characterized as of type string.

Storage Format

Consider both NCZarr and Zarr, and assume S3 notions of bucket
and object. In both systems, Groups and Variables (Array in Zarr)
map to S3 objects. Containment is modelled using the fact that
the container's key is a prefix of the variable's key.
So for example, if variable v1 is contained int top level group g1 – _/g1 –
then the key for v1 is /g1/v.
Additional information is stored in special objects whose name
start with ".z".
In Zarr, the following special objects exist.

  1. Information about a group is kept in a special object named
    .zgroup; so for example the object /g1/.zgroup.
  2. Information about an array is kept as a special object named .zarray;
    so for example the object /g1/v1/.zarray.
  3. Group-level attributes and variable-level attributes are stored
    in a special object named .zattr;
    so for example the objects /g1/.zattr and _/g1/v1/.zattr.

The NCZarr format uses the same group and variable (array) objects
as Zarr. It also uses the Zarr special .zXXX objects.

However, NCZarr adds some additional special objects.

  1. .nczarr – this is in the top level group – key /.nczarr.
    It is in effect the "superblock" for the dataset and contains
    any netcdf specific dataset level information.

  2. .nczgroup – this is a parallel object to .zgroup and contains
    any netcdf specific group information. Specifically it contains the following.

    • dims – the name and size of shared dimensions defined in this group.
    • vars – the name of variables defined in this group.
    • groups – the name of sub-groups defined in this group.

    These lists allow walking the NCZarr dataset without having to use
    the potentially costly S3 list operation.

  3. .nczvar – this is a parallel object to .zarray and contains
    netcdf specific information. Specifically it contains the following.

    • dimrefs – the names of the shared dimensions referenced by the variable.
    • storage – indicates if the variable is chunked vs contiguous
      in the netcdf sense.
      1 .nczattr – this is parallel to the .zattr objects and stores
      the attribute type information.

Translation

With some constraints, it is possible for an nczarr library to read
Zarr and for a zarr library to read the nczarr format.

The latter case, zarr reading nczarr is possible if the zarr library
is willing to ignore objects whose name it does not recognized;
specifically anthing beginning with .ncz.

The former case, nczarr reading zarr is also
possible if the nczarr can simulate or infer the contents of
the missing .nczXXX objects. As a rule this can be done as follows.

  1. .nczgroup – The list of contained variables and sub-groups
    can be computed using the S3 list operation to list the keys
    "contained" in the key for a group. By looking for occurrences
    of .zgroup, .zattr, _.zarray to infer the keys for the
    contained groups, attribute sets, and arrays (variables).
    Constructing the set of "shared dimensions" is carried out
    by walking all the variables in the whole dataset and collecting
    the set of unique integer shapes for the variables.
    For each such dimension length, a top level dimension is created
    named ".zdim<len>" where len is the integer length. The name
    is subject to change.
  2. .nczvar – The dimrefs are inferred by using the shape
    in .zarray and creating references to the simulated shared dimension.
    netcdf specific information.
  3. .nczattr – The type of each attribute is inferred by trying to parse the first attribute value string.

Examples {#nczarr_examples}

Here are a couple of examples using the ncgen and ncdump utilities.

  1. Create an nczarr file using a local directory tree as storage. 
    ​​​​ncgen -4 -lb -o "file:///home/user/dataset.nzf#mode=nczarr" dataset.cdl
  2. Display the content of an nczarr file using a local directory tree as storage. 
    ​​​​ncdump "file:///home/user/dataset.nzf#mode=nczarr"
  3. Create an nczarr file using S3 as storage. 
    ​​​​ncgen -4 -lb -o "s3://datasetbucket" dataset.cdl
  4. Create an nczarr file using S3 as storage and keeping to the pure
    zarr format. 
    ​​​​ncgen -4 -lb -o "s3://datasetbucket#mode=zarr" dataset.cdl

References {#nczarr_bib}

[1] Amazon Simple Storage Service Documentation

[2] NetCDF ZARR Data Model Specification

[3] Python Documentation: 8.3. collections — High-performance container datatypes

[4] Zarr Version 2 Specification

Appendix A. Building aws-sdk-cpp {#nczarr_s3sdk}

In order to use the S3 storage driver, it is necessary to
install the Amazon aws-sdk-cpp library.

As a starting point, here are the CMake options used by Unidata
to build that library. It assumes that it is being executed
in a build directory, build say, and that build/../CMakeLists.txt exists.

cmake -DFORCE_CURL=ON -DBUILD_ONLY=s3 -DMINIMIZE_SIZE=ON -DBUILD_DEPS=OFF -DCMAKE_CXX_STANDARD=14 ..

Appendix B. Amazon S3 Imposed Limits {#nczarr_s3limits}

The Amazon S3 cloud storage imposes some significant limits
that are inherited by NCZarr (and Zarr also, for that matter).

Some of the relevant limits are as follows:

  1. The maximum object size is 5 Gigabytes with a total
    for all objects limited to 5 Terabytes.
  2. S3 key names can be any UNICODE name with a maximum length of 1024
    characters. It is unclear if the 1024 refers to unicode characters or
    8-bit bytes (codepoints). This affect the depth to which groups can be
    nested because the key encodes the full path name of a group.

Point of Contact {#nczarr_poc}

Author: Dennis Heimbigner

Email: dmh at ucar dot edu

Initial Version: 4/10/2020

Last Revised: 4/12/2020

Last changed by 
 
Ryan Abernathey
Oceanographer and open-source hacker
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