Returns all records as a [RecordBatch] # Example: ```rust async { df.collect().await?; } ```

Returns a [Column] based on the given column name.

Creates a [Column] of [spark::expression::Literal] value.

Projects a set of expressions and returns a new [DataFrame] # Arguments: `cols` - An iterable of values that can be Columns # Example: ```rust asyn

Spark Connection gRPC client interface

Build the Spark [spark::Plan] for a [Relation]

Interface through which the user may create, drop, alter or query underlying databases, tables, functions, etc.

Create a [DataFrame] with a spingle column named `id`, containing elements in a range from `start` (default 0) to `end` (exclusive) with a step value

Returns a [DataFrameReader] that can be used to read datra in as a [DataFrame]

Returns a [DataFrame] representing the result of the given query

Specifies the input data source format

Attempt to connect to a remote Spark Session and return a [SparkSession]

Returns a [DataFrameWriter] struct based on the current [DataFrame]

Specifies the input data source format

Loads data from a data source and returns it as a [DataFrame] Example: ```rust let path = vec!["some/dir/path/on/the/remote/cluster/"]; // returns a

Create a relation from an existing [LogicalPlanBuilder] this will add additional actions to the [Relation]

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

Add an input option for the underlying data source

Equality comparion. Cannot overload the '==' and return something other than a bool

Specifies the behavior when data or table already exists # Arguments: - `mode`: [SaveMode] enum from the protobuf

Add an input option for the underlying data source

Returns the number of rows in this [DataFrame]

Returns a [DataFrameReader] that can be used to read datra in as a [DataFrame]

Start a streaming job to save the contents of the [StreamingQuery] to a data source. The data source is specified by the `format` and a set of `optio

Interface for [DataStreamWriter] to save the content of the streaming DataFrame out into external storage.

Returns a new [DataFrame] with an alias set.

Append a new field onto the exist fields

Checks if the DataFrame is empty and returns a boolean value.

Returns the first row as a RecordBatch.

Defines a windowing column # Arguments: `window`: a [WindowSpec] # Example ``` let window = Window::new() .partition_by([col("name")]) .order_by([c

Save the contents of the [DataFrame] to a data source. The data source is specified by the `format` and a set of `options`.

Retrieves the names of all columns in the [DataFrame] as a `Vec<String>`. The order of the column names in the list reflects their order in the [DataF

[RunTimeConfig] configuration interface for Spark.

Joins with another [DataFrame], using the given join expression. # Example: ```rust use spark_connect_rs::functions::col; use spark_connect_rs::dataf

Limits the result count o thte number specified and returns a new [DataFrame] # Example: ```rust async { df.limit(10).collect().await?; } ```

Prints the first `n` rows to the console # Arguments: `num_row`: (int, optional) number of rows to show (default 10) `truncate`: (int, optional) If

Compute aggregates and returns the result as a [DataFrame]

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

Returns the schema of this [DataFrame] as a [spark::DataType] which contains the schema of a [DataFrame]

Session ID

Returns a new [DataFrame] sorted by the specified column(s).

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

Check if the table or view with the specified name exists.

Counts the number of records for each group.

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

Returns a new [DataFrame] omitting rows with null values.

Filters rows using a given conditions and returns a new [DataFrame] # Example: ```rust async { df.filter("salary > 4000").collect().await?; } ```

Groups the [DataFrame] using the specified columns, and returns a [GroupedData] object

Reads data from JSON files with the specified options.

Specifies the behavior when data or table already exists # Arguments: - `output_mode`: [OutputMode] enum

Returns a [StreamingQueryManager] that allows managing all the StreamingQuery instances active on this context.

Computes the sum for each numeric columns for each group.

Query trigger for data to be processed by

Logical AND comparion. Cannot overload the '&&' and return something other than a bool

Reads data from CSV files with the specified options.