chore: update readme & examples

README.md

@@ -11,69 +11,56 @@ Currently, the Spark Connect client for Rust is **highly experimental** and **sh
 not be used in any production setting**. This is currently a "proof of concept" to identify the methods
 of interacting with Spark cluster from rust.
 
-## Quick Start
-
 The `spark-connect-rs` aims to provide an entrypoint to [Spark Connect](https://spark.apache.org/docs/latest/spark-connect-overview.html), and provide *similar* DataFrame API interactions.
 
+## Getting Started
+
+This section explains how run Spark Connect Rust locally starting from 0.
+
+Step 1: Install rust via rustup: https://www.rust-lang.org/tools/install
+
+Step 2: Ensure you have a [cmake](https://cmake.org/download/) and [protobuf](https://grpc.io/docs/protoc-installation/) install on your machine
+
+Step 3: Run the following commands to clone the repo
+
 ```bash
-docker compose up --build -d
-```
+git clone https://github.com/sjrusso8/spark-connect-rs.git
+git submodule update --init --recursive
 
-```rust
-use spark_connect_rs;
-
-use spark_connect_rs::{SparkSession, SparkSessionBuilder};
-
-use spark_connect_rs::functions as F;
-
-#[tokio::main]
-async fn main() -> Result<(), Box<dyn std::error::Error>> {
-    let spark: SparkSession = SparkSessionBuilder::remote("sc://127.0.0.1:15002/")
-            .build()
-            .await?;
-
-    let df = spark
-        .sql("SELECT * FROM json.`/opt/spark/examples/src/main/resources/employees.json`")
-        .await?;
-
-    df.filter("salary >= 3500")
-        .select(F::col("name"))
-        .show(Some(5), None, None)
-        .await?;
-
-    // +-------------+
-    // | show_string |
-    // +-------------+
-    // | +------+    |
-    // | |name  |    |
-    // | +------+    |
-    // | |Andy  |    |
-    // | |Justin|    |
-    // | |Berta |    |
-    // | +------+    |
-    // |             |
-    // +-------------+
-
-    Ok(())
-}
+cargo build
 ```
 
-## Getting Started
+Step 4: Setup the Spark Driver on localhost either by downloading spark or docker compose.
+
+With spark download:
+
+1. [Download Spark distribution](https://spark.apache.org/downloads.html) (3.4.0+), unzip the package.
+
+2. Start the Spark Connect server with the following command (make sure to use a package version that matches your Spark distribution):
 
 ```
-git clone https://github.com/sjrusso8/spark-connect-rs.git
-git submodule update --init --recursive
+sbin/start-connect-server.sh --packages org.apache.spark:spark-connect_2.12:3.4.0
+```
 
+With docker compose:
+
+1. Start the Spark Connect server by leveraging the created `docker-compose.yml` in this repo. This will start a Spark Connect Server running on port 15002
+
+```bash
 docker compose up --build -d
+```
+
+Step 5: Run an example from the repo under `/examples`
 
-cargo build && cargo test
+```bash
+cargo run --example sql
 ```
 
 ## Features
 
 The following section outlines some of the larger functionality that are not yet working with this Spark Connect implementation.
 
-- ![done] TLS authentication & Databricks compatability
+- ![done] TLS authentication & Databricks compatability via the feature flag `feature = 'tls'`
 - ![open] StreamingQueryManager
 - ![open] Window and ~~Pivot~~ functions
 - ![open] UDFs or any type of functionality that takes a closure (foreach, foreachBatch, etc.)

examples/databricks.rs

@@ -1,17 +1,19 @@
-// This example demonstrates connecting to a Databricks Cluster via a
-// tls connection.
+// This example demonstrates connecting to a Databricks Cluster via a tls connection.
 //
 // This demo requires access to a Databricks Workspace, a personal access token,
 // and a cluster id. The cluster should be running a 13.3LTS runtime or greater. Populate
 // the remote URL string between the `<>` with the appropriate details.
 //
+// The Databricks workspace instance name is the same as the Server Hostname value for your cluster.
+// Get connection details for a Databricks compute resource via https://docs.databricks.com/en/integrations/compute-details.html
+//
 // To view the connected Spark Session, go to the cluster Spark UI and select the 'Connect' tab.
 
 use spark_connect_rs::{SparkSession, SparkSessionBuilder};
 
 #[tokio::main]
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
-    let spark: SparkSession = SparkSessionBuilder::remote("sc://<workspace id>:443/;token=<personal access token>;x-databricks-cluster-id=<cluster-id>")
+    let spark: SparkSession = SparkSessionBuilder::remote("sc://<workspace instance name>:443/;token=<personal access token>;x-databricks-cluster-id=<cluster-id>")
         .build()
         .await?;
 

examples/delta.rs

@@ -12,7 +12,9 @@ use spark_connect_rs::dataframe::SaveMode;
 
 #[tokio::main]
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
-    let spark: SparkSession = SparkSessionBuilder::default().build().await?;
+    let spark: SparkSession = SparkSessionBuilder::remote("sc://127.0.0.1:15002/")
+        .build()
+        .await?;
 
     let paths = ["/opt/spark/examples/src/main/resources/people.csv"];
 

examples/reader.rs

@@ -1,10 +1,11 @@
+// This example demonstrates creating a Spark DataFrame from a CSV with read options
+// and then adding transformations for 'select' & 'sort'
+// printing the results as "show(...)"
+
 use spark_connect_rs::{SparkSession, SparkSessionBuilder};
 
 use spark_connect_rs::functions as F;
 
-// This example demonstrates creating a Spark DataFrame from a CSV with read options
-// and then adding transformations for 'select' & 'sort'
-// printing the results as "show(...)"
 #[tokio::main]
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
     let spark: SparkSession = SparkSessionBuilder::default().build().await?;

examples/readstream.rs

@@ -9,7 +9,7 @@ use std::{thread, time};
 #[tokio::main]
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
     let spark: SparkSession =
-        SparkSessionBuilder::remote("sc://127.0.0.1:15002/;user_id=example_rs")
+        SparkSessionBuilder::remote("sc://127.0.0.1:15002/;user_id=stream_example")
             .build()
             .await?;
 

examples/sql.rs

@@ -1,38 +1,43 @@
-use spark_connect_rs;
+// This example demonstrates creating a Spark DataFrame from a SQL command
+// and saving the results as a parquet and reading the new parquet file
 
+use spark_connect_rs::dataframe::SaveMode;
 use spark_connect_rs::{SparkSession, SparkSessionBuilder};
 
-// This example demonstrates creating a Spark DataFrame from a SQL command
-// and leveraging &str input for `filter` and `select` to change the dataframe
-// Displaying the results as "show(...)"
 #[tokio::main]
 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 spark: SparkSession = SparkSessionBuilder::remote("sc://127.0.0.1:15002/")
+        .build()
+        .await?;
 
     let df = spark
-        .sql("SELECT * FROM json.`/opt/spark/examples/src/main/resources/employees.json`")
+        .clone()
+        .sql("select 'apple' as word, 123 as count")
         .await?;
 
-    df.filter("salary >= 3500")
-        .select("*")
-        .show(Some(5), None, None)
+    df.write()
+        .mode(SaveMode::Overwrite)
+        .format("parquet")
+        .save("file:///tmp/spark-connect-write-example-output.parquet")
         .await?;
 
-    // +-----------------+
-    // | show_string     |
-    // +-----------------+
-    // | +------+------+ |
-    // | |name  |salary| |
-    // | +------+------+ |
-    // | |Andy  |4500  | |
-    // | |Justin|3500  | |
-    // | |Berta |4000  | |
-    // | +------+------+ |
-    // |                 |
-    // +-----------------+
+    let df = spark
+        .read()
+        .format("parquet")
+        .load(["file:///tmp/spark-connect-write-example-output.parquet"])?;
+
+    df.show(Some(100), None, None).await?;
+
+    // +---------------+
+    // | show_string   |
+    // +---------------+
+    // | +-----+-----+ |
+    // | |word |count| |
+    // | +-----+-----+ |
+    // | |apple|123  | |
+    // | +-----+-----+ |
+    // |               |
+    // +---------------+
 
     Ok(())
 }

examples/writer.rs

@@ -11,7 +11,9 @@ use spark_connect_rs::dataframe::SaveMode;
 // then reading the csv file back
 #[tokio::main]
 async fn main() -> Result<(), Box<dyn std::error::Error>> {
-    let spark: SparkSession = SparkSessionBuilder::default().build().await?;
+    let spark: SparkSession = SparkSessionBuilder::remote("sc://127.0.0.1:15002/")
+        .build()
+        .await?;
 
     let df = spark
         .clone()