Fetch n rows of a LazyFrame

Usage

fetch(
  .data,
  n_rows = 500,
  type_coercion = TRUE,
  predicate_pushdown = TRUE,
  projection_pushdown = TRUE,
  simplify_expression = TRUE,
  slice_pushdown = TRUE,
  comm_subplan_elim = TRUE,
  comm_subexpr_elim = TRUE,
  cluster_with_columns = TRUE,
  no_optimization = FALSE,
  engine = c("auto", "in-memory", "streaming"),
  streaming = FALSE
)

Arguments

.data

A Polars LazyFrame

n_rows

Number of rows to fetch.

type_coercion

Coerce types such that operations succeed and run on minimal required memory (default is TRUE).

predicate_pushdown

Applies filters as early as possible at scan level (default is TRUE).

projection_pushdown

Select only the columns that are needed at the scan level (default is TRUE).

simplify_expression

Various optimizations, such as constant folding and replacing expensive operations with faster alternatives (default is TRUE).

slice_pushdown

Only load the required slice from the scan. Don't materialize sliced outputs level. Don't materialize sliced outputs (default is TRUE).

comm_subplan_elim

Cache branching subplans that occur on self-joins or unions (default is TRUE).

comm_subexpr_elim

Cache common subexpressions (default is TRUE).

cluster_with_columns

Combine sequential independent calls to $with_columns().

no_optimization

Sets the following optimizations to FALSE: predicate_pushdown, projection_pushdown, slice_pushdown, simplify_expression. Default is FALSE.

engine

The engine name to use for processing the query. One of the followings:

• "auto" (default): Select the engine automatically. The "in-memory" engine will be selected for most cases.

• "in-memory": Use the in-memory engine.

• "streaming": Use the streaming engine, usually faster and can handle larger-than-memory data.

streaming

Deprecated, use engine instead.

Details

The parameter n_rows indicates how many rows from the LazyFrame should be used at the beginning of the query, but it doesn't guarantee that n_rows will be returned. For example, if the query contains a filter or join operations with other datasets, then the final number of rows can be lower than n_rows. On the other hand, appending some rows during the query can lead to an output that has more rows than n_rows.

See also