pal.rst

PAL: Product Access Layer

Table of Contents

Product Access Layer allows data stored logical "pools" to be accessed with light weight product refernces by data processers, data storage, and data consumers. A data product can include a context built with references of relevant data. A ProductStorage interface is provided to handle saving/retrieving/querying data in registered pools.

Rationale

In a data processing pipeline or network of processing nodes, data products are generated within a context which may include input data, reference data, and auxiliary data of many kind. It is often needed to have relevant context recorded with a product. However the context could have a large size so including their actual data as metadata of the product is often impractical.

Once FDI data are generated they can have a reference through which they can be accessed. The size of such references are typically less than a few hundred bytes, like a URL. In the product context only data references are recorded.

This package provides MapContext, ProductRef, Urn, ProductStorage, ProductPool, and Query classes (simplified but mostly API-compatible with Herschel Common Science System v15.0) for the storing, retrieving, tagging, and context creating of data product modeled in the dataset package.

Definitions

URN

fdi.pal.urn

Note

The following is from Urn

Note

The following is from parse_poolurl

ProductRef

This class not only holds the URN of the product it references to, but also records who ( the _parents) are keeping this reference.

ProductStorage

A centralized access place for saving/loading/querying/deleting data organized in conceptual pools. One gets a ProductRef when saving data.

ProductPool

An place where products can be saved, with a reference for the saved product generated. The product can be retrieved with the reference. Pools based on different media or networking mechanism can be implemented. Multiple pools can be registered in a ProductStorage front-end where users can do the saving, loading, querying etc. so that the pools are collectively form a larger logical storage.

The reference LocalPool is shown in the following YAML-like schematic:

Pool:!!dict
       _classes:!!odict
           product0_class_name:!!dict
                   currentSN:!!int #the serial number of the latest added prod to the pool
                          sn:!!list
                              - serial number of a prod
                              - serial number of a prod
                              - ...
           product1_class_name:
           ...
       _urns:!!odict
           urn0:!!odict
                   meta:!!MetaData #prod.meta
                   tags:!!list
                         - $tag
                         - $tag
                         - ...
           urn1:!!odict
       ...
       _tags:!!odict
           tag0:!!odict
                   urns:!!list
                        - $urn
                        - $urn
                        - ...
           tag1:!!odict
       ...

   urn0:!!serialized product
   urn1:!!serialized product
   ...

Examples (from quickstart page):

Context and MapContext

Context is a Product that holds a set of ProductRef s that accessible by keys. The keys are strings for MapContext which usually maps names to product references.

Examples (from quickstart page):

Query

One can make queries to a ProductStorage and get back a list of references to products that satisfy search chriteria. Queries can be constructed using Python predicate expressions about a product and its metadata, or a function that returns True or False.

Examples (from quickstart page):

run tests

To test PAL functionalities based on local (JSON) pool and memory pool, run in the same directory:

make test2

To test functionalities based on http client pool, in one terminal run

make runpoolserver

run

make testhttp

examine output.

Design

Packages

Classes