Prints the [spark::Plan] to the console # Arguments: `mode`: [ExplainMode] Defaults to `unspecified` - `simple` - `extended` - `codegen` - `cost` - `

Returns the first n rows.

Reads data from ORC files with the specified options.

Reads data from Parquet files with the specified options.

Saves the context of the [DataFrame] as the specified table.

Return the session ID

Reads data from text files with the specified options.

Returns a new [DataFrame] by adding multiple columns or replacing the existing columns that have the same names.

Add a tag to be assigned to all the operations started by this thread in this session.

sort functions Returns a sort expression based on the ascending order of the given column name.

Returns a sorted expression based on the ascending order of the column # Example: ```rust let df: DataFrame = df.sort([col("id").asc()]); let df: Da

Assign an issue to a user, which is a shorthand for jira.client.JIRA.assign_issue. The original one has an issue that it will search users ag

A boolean expression that is evaluated to `true` if the value is in the Column # Arguments: `cols`: a col reference that is translated into an [spar

Calculate the sample covariance for the given columns, specified by their names, as a f64

Creates or replaces a global temporary view using the given name.

Check if the database with the specified name exists.

Returns a new [DataFrame] containing the distinct rows in this [DataFrame].

Returns a new [DataFrame] without the specified columns

Return a new [DataFrame] with duplicate rows removed, optionally only considering certain columns from a `Vec<String>` If no columns are supplied the

A filter expression that evaluates if the column endswith a string literal

Replace null values, alias for `df.na().fill()`.

Get the tags that are currently set to be assigned to all the operations started by this thread.

Returns true if the table is currently cached in-memory.

Indicates whether the configuration property with the given key is modifiable in the current session.

A boolean expression that is evaluated to `true` if the value of the expression is contained by the evaluated values of the arguments # Arguments: `

Returns a list of columns for the given tables/views in the specific database

An alias for the function `alias`

Pivots a column of the current [DataFrame] and perform the specified aggregation

Prints out the schema in the tree format to a specific level number.

Sets the given Spark runtime configuration property.

Sets the current default catalog in this session

Returns the specific table as a [DataFrame] # Arguments: `table_name`: &str of the table name `options`: (optional Hashmap) contains additional read

Converts a [DataFrame] into String representation of JSON Each row is turned into a JSON document

Unpivot a DataFrame from wide format to long format, optionally leaving identifier columns set. This is the reverse to groupBy(…).pivot(…).agg(…), exc

Returns a new [DataFrame] by adding a column or replacing the existing column that has the same name.

Returns the column with a new name # Example: ```rust let cols = [ col("name").alias("new_name"), col("age").alias("new_age") ]; df.select(cols); ``

Sets a name for the application, which will be shown in the Spark web UI.

Computes average values for each numeric columns for each group.

Persists the [DataFrame] with the default [storage::StorageLevel::MemoryAndDiskDeser] (MEMORY_AND_DISK_DESER).

Caches the specified table in-memory or with given storage level.

Casts the column into the Spark DataType # Arguments: `to_type` is a string or [crate::types::DataType] of the target type # Example: ```rust use c

Prompt the user to choose who to assign the issue to in jira, given a list of candidates, including the original reporter and all commentator

Clear the current thread’s operation tags.

Returns a new [DataFrame] that has exactly `num_partitions` partitions.

Selects column based on the column name specified as a regex and returns it as [Column].

Sets a config option.

Calculates the correlation of two columns of a [DataFrame] as a `f64`. Currently only supports the Pearson Correlation Coefficient.

Creates a table based on the dataset in a data source.

Create a new map column.

Creates or replaces a local temporary view with this [DataFrame]

Returns the cartesian product with another [DataFrame].

Computes a pair-wise frequency table of the given columns. Also known as a contingency table.

Returns the current default catalog in this session

Returns the current default database in this session

Returns a sort expression based on the descending order of the given column name.

Computes basic statistics for numeric and string columns. This includes count, mean, stddev, min, and max. If no columns are given, this function comp

Drops the global temporary view with the given view name in the catalog.

Drops the local temporary view with the given view name in the catalog.

Returns all column names and their data types as a `Vec` containing the field name as a `String` and the [spark::data_type::Kind] enum

Return a new [DataFrame] containing rows in this [DataFrame] but not in another [DataFrame] while preserving duplicates.

Check if the function with the specified name exists.