Datacube

- Updated the way database indexes are patitioned. Run `datacube -v system init` to update indexes
- Added `fuse_data` ingester configuration parameter to control overlaping data fusion
- Added `--log-file` option to `datacube dataset add` command for saving logs to a file
- Added index.datasets.count method returning number of datasets matching the query

- Improved dataset search performance
- Restored ability to index telemetry data
- Fixed an issue with data access API returning uninitialized memory in some cases
- Fixed an issue where dataset center_time would be calculated incorrectly
- General improvements to documentation and usablity

- Added framework for developing distributed, task-based applications
- Several additional Ingester performance improvements

This release brings major performance and usability improvements
- Major performance improvements to `GridWorkflow` and Ingester
- Ingestion can be limited to one year at a time to limit memory usage
- Ingestion can be done in two stages (serial followed by highly parallel) by using `save-tasks`/`load-tasks` options.
This should help reduce idle time in distributed processing case.
- General improvements to documentation.

This release contains lots of fixes in preparation for the first large
ingestion of Geoscience Australia data into a production version of
AGDCv2.
- General improvements to documentation and user friendliness.
- Updated metadata in configuration files for ingested products.
- Full provenance history is saved into ingested files.
- Added software versions, machine info and other details of the
ingestion run into the provenance.
- Added valid data region information into metadata for ingested data.
- Fixed bugs relating to changes in Rasterio and GDAL versions.
- Refactored `GridWorkflow` to be easier to use, and include
preliminary code for saving created products.
- Improvements and fixes for bit mask generation.
- Lots of other minor but important fixes throughout the codebase.

This release includes restructuring of code, APIs, tools, configurations and concepts. The result of this churn is cleaner code, faster performance and the ability to handle provenance tracking of Datasets created within the Data Cube.

The major changes include:
- The datacube-config and datacube-ingest tools have been combined into datacube.
- Added dependency on pandas for nicer search results listing and handling.
- Indexing and Ingestion have been split into separate steps.
- Data that has been indexed can be accessed without going through the ingestion process.
- Data can be requested in any projection and will be dynamically reprojected if required.
- Storage Type has been removed, and an Ingestion Configuration has taken it’s place.
- A new Datacube class for querying and accessing data.