Struct spark_connect_rs::session::SparkSession

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pub struct SparkSession { /* private fields */ }
Expand description

The entry point to connecting to a Spark Cluster using the Spark Connection gRPC protocol.

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impl SparkSession

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pub fn new( client: SparkConnectClient<InterceptedService<Channel, MetadataInterceptor>> ) -> Self

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pub fn range( self, start: Option<i64>, end: i64, step: i64, num_partitions: Option<i32> ) -> DataFrame

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 step, and control the number of partitions with num_partitions

Examples found in repository?
examples/writer.rs (line 18)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession = SparkSessionBuilder::default().build().await?;

    let df = spark
        .clone()
        .range(None, 1000, 1, Some(16))
        .select(col("id").alias("range_id"));

    let path = "/opt/spark/examples/src/main/rust/employees/";

    df.write()
        .format("csv")
        .mode(SaveMode::Overwrite)
        .option("header", "true")
        .save(path)
        .await?;

    let df = spark
        .clone()
        .read()
        .format("csv")
        .option("header", "true")
        .load([path])?;

    df.show(Some(10), None, None).await?;

    // print results may slighty vary but should be close to the below
    // +--------------------------+
    // | show_string              |
    // +--------------------------+
    // | +--------+               |
    // | |range_id|               |
    // | +--------+               |
    // | |312     |               |
    // | |313     |               |
    // | |314     |               |
    // | |315     |               |
    // | |316     |               |
    // | |317     |               |
    // | |318     |               |
    // | |319     |               |
    // | |320     |               |
    // | |321     |               |
    // | +--------+               |
    // | only showing top 10 rows |
    // |                          |
    // +--------------------------+

    Ok(())
}
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pub fn read(self) -> DataFrameReader

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

Examples found in repository?
examples/reader.rs (line 15)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession = SparkSessionBuilder::default().build().await?;

    let path = ["/opt/spark/examples/src/main/resources/people.csv"];

    let df = spark
        .read()
        .format("csv")
        .option("header", "True")
        .option("delimiter", ";")
        .load(path)?;

    df.select([
        F::col("name"),
        F::col("age").cast("int").alias("age_int"),
        (F::lit(3.0) + F::col("age").cast("int")).alias("addition"),
    ])
    .sort(vec![F::col("name").desc()])
    .show(Some(5), None, None)
    .await?;

    // print results
    // +--------------------------+
    // | show_string              |
    // +--------------------------+
    // | +-----+-------+--------+ |
    // | |name |age_int|addition| |
    // | +-----+-------+--------+ |
    // | |Jorge|30     |33.0    | |
    // | |Bob  |32     |35.0    | |
    // | +-----+-------+--------+ |
    // |                          |
    // +--------------------------+

    Ok(())
}
More examples
Hide additional examples
examples/writer.rs (line 32)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession = SparkSessionBuilder::default().build().await?;

    let df = spark
        .clone()
        .range(None, 1000, 1, Some(16))
        .select(col("id").alias("range_id"));

    let path = "/opt/spark/examples/src/main/rust/employees/";

    df.write()
        .format("csv")
        .mode(SaveMode::Overwrite)
        .option("header", "true")
        .save(path)
        .await?;

    let df = spark
        .clone()
        .read()
        .format("csv")
        .option("header", "true")
        .load([path])?;

    df.show(Some(10), None, None).await?;

    // print results may slighty vary but should be close to the below
    // +--------------------------+
    // | show_string              |
    // +--------------------------+
    // | +--------+               |
    // | |range_id|               |
    // | +--------+               |
    // | |312     |               |
    // | |313     |               |
    // | |314     |               |
    // | |315     |               |
    // | |316     |               |
    // | |317     |               |
    // | |318     |               |
    // | |319     |               |
    // | |320     |               |
    // | |321     |               |
    // | +--------+               |
    // | only showing top 10 rows |
    // |                          |
    // +--------------------------+

    Ok(())
}
examples/delta.rs (line 21)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession = SparkSessionBuilder::default().build().await?;

    let paths = ["/opt/spark/examples/src/main/resources/people.csv"];

    let df = spark
        .clone()
        .read()
        .format("csv")
        .option("header", "True")
        .option("delimiter", ";")
        .option("inferSchema", "True")
        .load(paths)?;

    df.write()
        .format("delta")
        .mode(SaveMode::Overwrite)
        .saveAsTable("default.people_delta")
        .await?;

    spark
        .sql("DESCRIBE HISTORY default.people_delta")
        .await?
        .show(Some(1), None, Some(true))
        .await?;

    // print results
    // +-------------------------------------------------------------------------------------------------------+
    // | show_string                                                                                           |
    // +-------------------------------------------------------------------------------------------------------+
    // | -RECORD 0-------------------------------------------------------------------------------------------- |
    // |  version             | 3                                                                              |
    // |  timestamp           | 2024-03-16 13:46:23.552                                                        |
    // |  userId              | NULL                                                                           |
    // |  userName            | NULL                                                                           |
    // |  operation           | CREATE OR REPLACE TABLE AS SELECT                                              |
    // |  operationParameters | {isManaged -> true, description -> NULL, partitionBy -> [], properties -> {}}  |
    // |  job                 | NULL                                                                           |
    // |  notebook            | NULL                                                                           |
    // |  clusterId           | NULL                                                                           |
    // |  readVersion         | 2                                                                              |
    // |  isolationLevel      | Serializable                                                                   |
    // |  isBlindAppend       | false                                                                          |
    // |  operationMetrics    | {numFiles -> 1, numOutputRows -> 2, numOutputBytes -> 988}                     |
    // |  userMetadata        | NULL                                                                           |
    // |  engineInfo          | Apache-Spark/3.5.0 Delta-Lake/3.0.0                                            |
    // | only showing top 1 row                                                                                |
    // |                                                                                                       |
    // +-------------------------------------------------------------------------------------------------------+

    Ok(())
}
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pub fn readStream(self) -> DataStreamReader

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

Examples found in repository?
examples/readstream.rs (line 17)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession =
        SparkSessionBuilder::remote("sc://127.0.0.1:15002/;user_id=example_rs")
            .build()
            .await?;

    let df = spark
        .readStream()
        .format("rate")
        .option("rowsPerSecond", "5")
        .load(None)?;

    let query = df
        .writeStream()
        .format("console")
        .queryName("example_stream")
        .outputMode(OutputMode::Append)
        .trigger(Trigger::ProcessingTimeInterval("1 seconds".to_string()))
        .start(None)
        .await?;

    // loop to get multiple progression stats
    for _ in 1..5 {
        thread::sleep(time::Duration::from_secs(5));
        let val = &query.clone().lastProgress().await?;
        println!("{}", val);
    }

    // stop the active stream
    query.stop().await?;

    Ok(())
}
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pub fn table(self, name: &str) -> Result<DataFrame, SparkError>

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pub fn catalog(self) -> Catalog

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

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pub async fn sql(self, sql_query: &str) -> Result<DataFrame, SparkError>

Returns a DataFrame representing the result of the given query

Examples found in repository?
examples/sql.rs (line 16)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession =
        SparkSessionBuilder::remote("sc://127.0.0.1:15002/;user_id=example_rs")
            .build()
            .await?;

    let df = spark
        .sql("SELECT * FROM json.`/opt/spark/examples/src/main/resources/employees.json`")
        .await?;

    df.filter("salary >= 3500")
        .select("*")
        .show(Some(5), None, None)
        .await?;

    // +-----------------+
    // | show_string     |
    // +-----------------+
    // | +------+------+ |
    // | |name  |salary| |
    // | +------+------+ |
    // | |Andy  |4500  | |
    // | |Justin|3500  | |
    // | |Berta |4000  | |
    // | +------+------+ |
    // |                 |
    // +-----------------+

    Ok(())
}
More examples
Hide additional examples
examples/delta.rs (line 35)
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let spark: SparkSession = SparkSessionBuilder::default().build().await?;

    let paths = ["/opt/spark/examples/src/main/resources/people.csv"];

    let df = spark
        .clone()
        .read()
        .format("csv")
        .option("header", "True")
        .option("delimiter", ";")
        .option("inferSchema", "True")
        .load(paths)?;

    df.write()
        .format("delta")
        .mode(SaveMode::Overwrite)
        .saveAsTable("default.people_delta")
        .await?;

    spark
        .sql("DESCRIBE HISTORY default.people_delta")
        .await?
        .show(Some(1), None, Some(true))
        .await?;

    // print results
    // +-------------------------------------------------------------------------------------------------------+
    // | show_string                                                                                           |
    // +-------------------------------------------------------------------------------------------------------+
    // | -RECORD 0-------------------------------------------------------------------------------------------- |
    // |  version             | 3                                                                              |
    // |  timestamp           | 2024-03-16 13:46:23.552                                                        |
    // |  userId              | NULL                                                                           |
    // |  userName            | NULL                                                                           |
    // |  operation           | CREATE OR REPLACE TABLE AS SELECT                                              |
    // |  operationParameters | {isManaged -> true, description -> NULL, partitionBy -> [], properties -> {}}  |
    // |  job                 | NULL                                                                           |
    // |  notebook            | NULL                                                                           |
    // |  clusterId           | NULL                                                                           |
    // |  readVersion         | 2                                                                              |
    // |  isolationLevel      | Serializable                                                                   |
    // |  isBlindAppend       | false                                                                          |
    // |  operationMetrics    | {numFiles -> 1, numOutputRows -> 2, numOutputBytes -> 988}                     |
    // |  userMetadata        | NULL                                                                           |
    // |  engineInfo          | Apache-Spark/3.5.0 Delta-Lake/3.0.0                                            |
    // | only showing top 1 row                                                                                |
    // |                                                                                                       |
    // +-------------------------------------------------------------------------------------------------------+

    Ok(())
}
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pub fn createDataFrame( self, data: &RecordBatch ) -> Result<DataFrame, SparkError>

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pub fn session_id(&self) -> &str

Return the session ID

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pub fn client( self ) -> SparkConnectClient<InterceptedService<Channel, MetadataInterceptor>>

Spark Connection gRPC client interface

Trait Implementations§

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impl Clone for SparkSession

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fn clone(&self) -> SparkSession

Returns a copy of the value. Read more
1.0.0 · source§

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for SparkSession

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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