Spark stores data in resilient distributed datasets (RDDs), a read-only, lazily evaluated, partitioned collections of records.
We then partitioned our collection of 4679 footprints into two subsets: (i) 1724 ones that contain a known protein-binding motif at q-value <0.05, called known footprints; and (ii) 2955 ones that do not, called unknown footprints.
Twenty-seven percent of the total molecular variance was due to difference between the two germplasm groups, whereas 73% was partitioned within collections.
Let's put aside the whole problem of partitioning a collection of mostly 19th- and 20th-century art in terms of geography, ethnicity or gender at a time when prominent institutions like the Whitney Museum of American Art and the Studio Museum in Harlem are trying to expand beyond such definitions.
In particular, we use the K-means clustering which partitions a collection of n objects into k distinct and non-empty clusters where data being grouped in an exclusive way, that is, each object will belong to a single cluster.
Additionally, the NJ and STRUCTURE analyses agreed in partitioning the collection into six sub-groups, with few differences among sub-groups.
The complex nonlinear appearance manifold of each registered person is partitioned into a collection of submanifolds where each models the face appearances of the person in nearby poses.
J. Baker et al., presented Megastore [8] in which data is partitioned into a collection of entity groups.
The complete set of resulting defaults from K can be partitioned into a collection of subsets of defaults, where defaults in a given subset have the same consequence.
To implement the H strategy we partitioned the entire collection in K = 4 groups composed respectively of 83, 99, 114 and 50 individuals.
