Data Tables / Data Collections

In the Beacon Data Lake, data is organized into tables (also referred to as data collections). Each table contains a set of columns originating from the datasets stored inside the data lake. You can interact with these tables using the beacon_api package to perform queries and retrieve data. Each table is represented by a Table object in the beacon_api package. You can obtain a Table object by listing the available tables in the connected Beacon Data Lake using the list_tables method of the Client object.

tables = client.list_tables()
print(tables)  # This will print a dictionary of available tables

You can access a specific table by its name from the dictionary returned by list_tables. For example, to access a table named vessels, you can do the following:

vessels_table = tables['vessels']
print(vessels_table)  # This will print the Table object for the 'vessels' table

Once you have a Table object, you can view its schema (available columns) using the get_table_schema method:

schema = vessels_table.get_table_schema()
print(schema)  # This will print the schema of the 'vessels' table

You can also create and execute queries on the table using the query method of the Table object. This will return a Query object that you can use to build and execute your query.

query = vessels_table.query()
# You can then build your query using the Query methods