GffDataSource
Related Docs:
object GffDataSource
| package gff
Saves a DataFrame to a destination (not supported in this DataSource.)
Saves a DataFrame to a destination (not supported in this DataSource.)
Creates relation with user schema.
Creates relation with user schema. User-specified schema can have a subset of attribute columns as they will be parsed out of "attributes" column
spark sql context
parameters for job
user defined schema
Base relation
Creates relation
Creates relation
spark sql context
parameters for job
Base relation
Gff data source to read GFF3 files.
The data source is able to infer the schema or accept a user-specified schema. It flattens the attributes field by creating a column for each tag that appears in the attributes column of the gff file.
The inferred schema will have base fields corresponding to the first 8 columns of gff3 called seqId, source, type, start, end, score, strand, and phase, followed by any official attribute field among id, name, alias, parent, target, gap, derivesfrom, note, dbxref, ontologyterm, and iscircular that appears in the gff tags followed by any unofficial attribute field that appears in the tags. In the inferred schema, the base and official fields will be in the same order as listed above. The unofficial fields will be in alphabetical order.
Any user-specified schema can have any subset of fields corresponding to the 9 columns of gff3 (named seqId, source, type, start, end, score, strand, phase, and attributes), the official attribute fields, and the unofficial attribute fields. The name of the official and unofficial fields should match the tag name in a case-and-underscore-insensitive fashion.