sql_io.py: put_table(): Add pkey on pkeys table right when it's created, so that any duplicates are detected right away instead of at the end of the iteration. (Duplicates are created as a result of joins matching multiple rows, which often indicates a database misconfiguration.)

sql_io.py: put_table(): Adding pkey on pkeys table: Removed log message because adding an index is considered a low-level operation, which isn't included in the Redmine SQL

schemas/tree_cross-links.sql: Ancestors table: Synced with current definition, which removes unneeded fki_* indexes. Note that the index on ancestor_id might be needed in the future if we ever want to get all the descendants of a plantname/namedplace or perform deletions on plantname/namedplace (which cascade to *_ancestor). For getting all the plantnames/namedplaces (of any rank) for a plantconcept/locationdetermination, though, the *_ancestor_pkey index is sufficient because plantname_id/namedplace_id is the first column in it.

schemas/vegbien.sql: {plantname,namedplace}_update_ancestors(): Fixed slowdown due to removed index on {plantname,namedplace}.parent_id by adding COALESCE to enable using the plantname_unique index for the lookup instead

sql.mk_select() calls: Removed no longer needed start=0 to turn off missing WHERE, LIMIT, or OFFSET clause warning

sql.py: mk_select(): Don't output warning if there is no WHERE, LIMIT, or OFFSET clause, because column-based import has many queries where this is the case and it's annoying to need to specify start=0 to turn off this warning

sql.py: flatten(): Don't sort the input tables by the pkey because it doesn't matter what order the datasource's rows are inserted in. Note that PostgreSQL doesn't guarantee the order of rows in a table, so it is possible that the rows were being inserted in an unknown order before this change, as well.

sql.py: delete(): Cache deletes by default

sql_io.py: put_table(): Merged remove_rows() and invalid2null() into one ignore() function that chooses the action (map to NULL or delete) depending on the value and whether NULLs have been filtered out of the column

sql_io.py: put_table(): remove_rows(): Delete the rows containing the invalid value instead of filtering them out of each select, so that the filtering can be profiled separately from the insertion. This also requires deleting rows with invalid non-NULL values instead of mapping them to NULL if NULLs have already been filtered out of the column in question.