User can access actual columns and path variables by creating a regular table on a SELECT query (Create Table as SELECT, CTAS) with each required column and path variables selected from the foreign table. Each path variable must be typecast to a valid type and then aliased to the appropriate column name. This allows user to access path variables along with Parquet data. It is up to the user on what must be selected in SELECT query passed to "DataFrame.from_query()": columns, attributes, keys from foreign table and path variables.
Example
Create a regular table.
# Let's see an example. Here is how we created a regular table from foreign table. """ CREATE TABLE t1lctas AS ( SELECT CAST($path.$var1 AS CHAR(10)) Var1, CAST($path.$var2 AS CHAR(4)) Var2, CAST($path.$var3 AS CHAR(2)) var3, CAST($path.$var4 AS CHAR(2)) Var4, a, b, c, d, e, f, g, h, i, j FROM t1l) WITH DATA PRIMARY INDEX(a) """
Create a DataFrame on the table and display the head of the DataFrame.
# Create a DataFrame on a table. >>> wrk2dfview = DataFrame("t1lctas") >>> wrk2dfview.head().to_pandas()
Var1 Var2 var3 Var4 b c d e f g h i j a 3 csoj_files t1l. None None 30 103 1 CScs 1961-06-05 300.333 19.0 4 10 5 csoj_files t1l. None None 50 105 1 CScs 1961-06-05 200.333 19.0 4 10 6 csoj_files t1l. None None 60 106 1 CScs 1963-02-03 300.333 19.0 4 10 7 csoj_files t1l. None None 70 107 1 CScs 1963-02-03 100.333 19.0 4 10 9 csoj_files t1l. None None 90 109 1 CScs 1963-02-03 300.333 19.0 4 10 10 csoj_files t1l. None None 100 110 1 CScs 1963-02-03 100.333 19.0 4 10 8 csoj_files t1l. None None 80 108 1 CScs 1963-02-03 200.333 19.0 4 10 4 csoj_files t1l. None None 40 104 1 CScs 1961-06-05 100.333 19.0 4 10 2 csoj_files t1l. None None 20 102 1 CScs 1961-06-05 200.333 19.0 4 10 1 csoj_files t1l. None None 10 101 1 CScs 1961-06-05 100.333 19.0 4 10