Uses of Class org.openrefine.runners.local.pll.PairPLL (OpenRefine 4.0-SNAPSHOT API)

Packages that use PairPLL
Package	Description
org.openrefine.runners.local	Supplies a `Runner` which is designed for execution on a single machine, with parallelism.
org.openrefine.runners.local.pll

Uses of PairPLL in org.openrefine.runners.local

Fields in org.openrefine.runners.local declared as PairPLL
Modifier and Type	Field	Description
`protected PairPLL<Long,IndexedRow>`	LocalGrid.`grid`
`protected PairPLL<Long,Record>`	LocalGrid.`records`

Methods in org.openrefine.runners.local that return PairPLL
Modifier and Type	Method	Description
`PairPLL<Long,IndexedData<T>>`	LocalChangeData.`getPLL()`
`protected PairPLL<Long,Record>`	LocalGrid.`records()`

Constructors in org.openrefine.runners.local with parameters of type PairPLL
Constructor	Description
`LocalChangeData(LocalRunner runner, PairPLL<Long,IndexedData<T>> grid, io.vavr.collection.Array<Long> parentPartitionSizes, Callable<Boolean> complete, int maxConcurrency)`	Constructs a change data.
`LocalGrid(LocalRunner runner, ColumnModel columnModel, PairPLL<Long,IndexedRow> grid, Map<String,OverlayModel> overlayModels, long cachedRecordCount)`	Constructs a grid, supplying all required fields.
`LocalGrid(LocalRunner runner, PairPLL<Long,Row> grid, ColumnModel columnModel, Map<String,OverlayModel> overlayModels, long cachedRecordCount)`	Convenience constructor to construct a grid from a PLL of a slightly different type.
`LocalGrid(PairPLL<Long,Record> records, LocalRunner runner, ColumnModel columnModel, Map<String,OverlayModel> overlayModels, long rowCount)`	Constructs a grid from a grid of records.

Uses of PairPLL in org.openrefine.runners.local.pll

Methods in org.openrefine.runners.local.pll that return PairPLL
Modifier and Type	Method	Description
`static <T> PairPLL<Long,T>`	PairPLL.`assumeIndexed(PairPLL<Long,T> pairPLL, long totalRowCount)`	Assuming that the keys of the PairPLL are indices, deduce the partition sizes from the first element of each partition and the total number of elements, creating an appropriate RangePartitioner and adding it to the PLL.
`static <T> PairPLL<Long,T>`	PairPLL.`assumeSorted(PairPLL<Long,T> pairPLL)`	Assumes that a PLL is sorted by key and derive the appropriate partitioner for it.
`PairPLL<K,V>`	PairPLL.`dropFirstElements(long n)`	Drops the first n elements at the beginning of the collection.
`PairPLL<K,V>`	PairPLL.`dropLastElements(long n)`	Drops the first n elements at the end of the collection.
`PairPLL<K,V>`	PairPLL.`filter(Predicate<? super Tuple2<K,V>> predicate)`
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`fullJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the full (outer) join of both PLLs.
`static PairPLL<Long,Record>`	RecordPLL.`groupIntoRecords(PairPLL<Long,IndexedRow> grid, int keyColumnIndex)`	Constructs an indexed PLL of records by grouping rows together.
`static <T> PairPLL<Long,T>`	IndexedPLL.`index(PLL<T> pll)`	Create an indexed PLL by indexing an existing PLL.
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`innerJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the inner join of both PLLs.
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`leftJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the left join of both PLLs.
`PairPLL<K,V>`	PairPLL.`limitPartitions(long limit)`
`<K,V> PairPLL<K,V>`	PLL.`mapToPair(Function<T,Tuple2<K,V>> mapFunction)`	Deprecated. use `PLL.mapToPair(Function, String)` to also provide a description of the map function applied
`<K,V> PairPLL<K,V>`	PLL.`mapToPair(Function<T,Tuple2<K,V>> mapFunction, String mapDescription)`	Maps this collection to an indexed PLL.
`<W> PairPLL<K,W>`	PairPLL.`mapValues(BiFunction<K,V,W> mapFunction, String mapDescription)`	Returns a PLL obtained by mapping each element and preserving the indexing.
`PairPLL<K,V>`	PairPLL.`retainPartitions(List<Integer> partitionIndices)`
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`rightJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the right join of both PLLs.
`PairPLL<K,V>`	PairPLL.`withCachedPartitionSizes(io.vavr.collection.Array<Long> newCachedPartitionSizes)`	Returns a copy of this PairPLL with the given partition sizes, when they are externally known.
`PairPLL<K,V>`	PairPLL.`withPartitioner(Optional<Partitioner<K>> partitioner)`	Returns a copy of this PairPLL with a changed partitioner.
`PairPLL<Long,T>`	PLL.`zipWithIndex()`	Indexes the collection in sequential order.

Methods in org.openrefine.runners.local.pll with parameters of type PairPLL
Modifier and Type	Method	Description
`static <T> PairPLL<Long,T>`	PairPLL.`assumeIndexed(PairPLL<Long,T> pairPLL, long totalRowCount)`	Assuming that the keys of the PairPLL are indices, deduce the partition sizes from the first element of each partition and the total number of elements, creating an appropriate RangePartitioner and adding it to the PLL.
`static <T> PairPLL<Long,T>`	PairPLL.`assumeSorted(PairPLL<Long,T> pairPLL)`	Assumes that a PLL is sorted by key and derive the appropriate partitioner for it.
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`fullJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the full (outer) join of both PLLs.
`static PairPLL<Long,Record>`	RecordPLL.`groupIntoRecords(PairPLL<Long,IndexedRow> grid, int keyColumnIndex)`	Constructs an indexed PLL of records by grouping rows together.
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`innerJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the inner join of both PLLs.
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`leftJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the left join of both PLLs.
`<W> PairPLL<K,Tuple2<V,W>>`	PairPLL.`rightJoinOrdered(PairPLL<K,W> other, Comparator<K> comparator)`	Assuming both PairPLLs are ordered by key, and each key appears at most once in each dataset, returns an ordered PairPLL with the right join of both PLLs.

Constructors in org.openrefine.runners.local.pll with parameters of type PairPLL
Constructor	Description
`OrderedJoinPLL(PairPLL<K,V> first, PairPLL<K,W> second, Comparator<K> comparator, OrderedJoinPLL.JoinType joinType)`	Constructs a PLL representing the join of two others
`RecordPLL(PairPLL<Long,IndexedRow> grid, int keyColumnIndex)`	Constructs a PLL of records by grouping rows together.