Package com.cupoftea.lazy

Interface LazyDataFrame

All Known Implementing Classes:
LazyCupOfTea
public interface LazyDataFrame
Enterprise lazy / streaming DataFrame evaluation interface for out-of-core data processing. Operations are recorded in an execution plan and executed across streaming chunks/partitions only when materialized via collect().

  • Method Details

    • filter

      LazyDataFrame filter(IFilter filter)
      Filters rows using an IFilter predicate during chunk processing.

    • filter

      LazyDataFrame filter(String column, Predicate<Object> predicate)
      Filters rows by evaluating a predicate against the specified column.

    • select

      LazyDataFrame select(String... columns)
      Projects only the specified columns, pruning unused columns early.

    • drop

      LazyDataFrame drop(String... columns)
      Drops the specified columns from the projection.

    • limit

      LazyDataFrame limit(long n)
      Limits evaluation to at most n rows, stopping chunk reads early.

    • head

      default LazyDataFrame head(long n)
      Alias for limit(long).

    • groupBy

      LazyGroupBy groupBy(String... columns)
      Groups by the specified column(s) for streaming group aggregations.

    • agg

      LazyDataFrame agg(Aggregate... aggregates)
      Aggregates the entire dataset across streaming chunks into a single-row DataFrame.

    • agg

      LazyDataFrame agg(Aggregation... aggregations)
      Aggregates the entire dataset across streaming chunks into a single-row DataFrame.

    • orderBy

      LazyDataFrame orderBy(String... columns)
      Orders the collected result DataFrame by the specified columns.

    • parallel

      LazyDataFrame parallel()
      Enables parallel execution across stream partitions.

    • parallel

      LazyDataFrame parallel(ExecutorService executor)
      Enables parallel execution using the specified ExecutorService.

    • sequential

      LazyDataFrame sequential()
      Forces sequential execution across stream partitions.

    • batchSize

      LazyDataFrame batchSize(int batchSize)
      Sets the batch size in rows for chunk processing.

    • chunkSize

      LazyDataFrame chunkSize(int chunkSizeBytes)
      Sets the chunk target size in bytes for partition slicing.

    • collect

      CupOfTea collect()
      Executes the streaming plan out-of-core and materializes the aggregated/filtered result CupOfTea DataFrame.

    • count

      long count()
      Counts the total number of matching rows in the streaming dataset without materializing full rows into memory.

    • getSchema

      Schema getSchema()
      Returns the schema of the source dataset.

    • getHeaders

      List<Column> getHeaders()
      Returns the column headers of the source dataset.

    • explain

      String explain()
      Returns a human-readable description of the lazy execution plan.