Spark/Scala: Load Spark data frame into CrateDB using Scala and HTTP (#520)

* New example with Scala Spark and the CrateDB http endpoint

* Typo

* Update by-language/scala-spark-http/README.md

Co-authored-by: Andreas Motl <andreas.motl@crate.io>

* Update by-language/scala-spark-http/README.md

Co-authored-by: Andreas Motl <andreas.motl@crate.io>

* Update by-language/scala-spark-http/README.md

Co-authored-by: Andreas Motl <andreas.motl@crate.io>

* Update by-language/scala-spark-http/README.md

Co-authored-by: Andreas Motl <andreas.motl@crate.io>

* Moving example to by-dataframe folder as suggested by amotl

---------

Co-authored-by: Andreas Motl <andreas.motl@crate.io>

Author: hlcianfagna

by-dataframe/spark/scala-http/README.md

@@ -0,0 +1,31 @@
+# Load Spark data frame into CrateDB using Scala and HTTP
+
+This example aims to demonstrate how a Spark data frame can be loaded into CrateDB using the CrateDB HTTP endpoint.
+
+It assumes there is a CrateDB instance running on localhost accepting connections with the default `crate` superuser, and it relies on the following table being created:
+
+.. code-block:: sql
+
+    CREATE TABLE myschema.mytable (
+        examplefield1   TIMESTAMP,
+        anotherfield    geo_point,
+        jsonpayload     OBJECT
+    );
+
+When applicable for your environment, you may want to consider to replace `scalaj.http` with async calls like `akka.http` or `AsyncHttpClient`.
+You may also want to explore if connection pooling is useful in your environment,
+and if JDBC calls leveraging the PostgreSQL wire protocol are more convenient
+for your particular case.
+
+Saying this, note that this example uses [CrateDB's HTTP bulk operations] to ingest
+data, which is currently the most efficient way to do it.
+
+[CrateDB's HTTP bulk operations]: https://cratedb.com/docs/guide/performance/inserts/bulk.html
+
+You can run this example with [sbt]:
+
+.. code-block:: shell
+
+    sbt run
+
+[sbt]: https://www.scala-sbt.org/download/

by-dataframe/spark/scala-http/SparkCrateDBhttpExample.scala

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+import scalaj.http.{Http, HttpOptions}
+import org.apache.spark.sql.{SparkSession, Row}
+import org.apache.spark.sql.types._
+import org.json4s.jackson.Serialization
+import java.time.LocalDateTime
+import java.time.format.DateTimeFormatter
+import java.sql.Timestamp
+
+object SparkCrateDBhttpExample {
+  def main(args: Array[String]): Unit = {
+    val formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm")
+	
+	val data = Seq(
+	  Row(Timestamp.valueOf(LocalDateTime.parse("2024-07-10 10:00", formatter)), Array(9.744417, 47.413417), """{"example_quantity_field": 30, "example_string_field": "abc"}"""),
+	  Row(Timestamp.valueOf(LocalDateTime.parse("2024-07-10 11:00", formatter)), Array(13.46738, 52.50463), """{"example_quantity_field": 40, "example_string_field": "def"}""")
+	)
+	
+	val spark = SparkSession.builder
+		.appName("test")
+		.master("local[*]") 
+		.getOrCreate()
+	val df = spark.createDataFrame(
+	  spark.sparkContext.parallelize(data),
+	  StructType(
+		List(
+		  StructField("examplefield1", TimestampType, true),
+		  StructField("anotherfield", ArrayType(DoubleType), true),
+		  StructField("jsonpayload", StringType, true)
+		)
+	  )
+	)
+	
+	val url = "http://localhost:4200/_sql"
+	
+	val columns = df.columns.mkString(", ")
+	val placeholders = df.columns.map(_ => "?").mkString(", ")
+	val stmt = s"INSERT INTO myschema.mytable ($columns) VALUES ($placeholders)"
+
+	val columnNames = df.columns
+	df.foreachPartition { partition =>  
+	  val bulkArgs: List[List[Any]] = partition.map { row =>
+		columnNames.indices.map(i => row.get(i)).toList
+	  }.toList
+
+	  if (bulkArgs.nonEmpty) {    
+		val data = Map(
+		  "stmt" -> stmt,
+		  "bulk_args" -> bulkArgs
+		)
+			
+		implicit val formats = org.json4s.DefaultFormats
+		val jsonString = Serialization.write(data)
+		
+		val response = Http(url)
+		  .postData(jsonString)
+		  .header("Content-Type", "application/json")      
+		  .asString
+		
+		println(response)
+	  }
+	}	
+  }
+}
+

by-dataframe/spark/scala-http/build.sbt

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+name := "SparkCrateDBhttpExample"
+
+version := "0.1"
+
+scalaVersion := "2.11.12"
+
+libraryDependencies ++= Seq(
+  "org.scala-lang.modules" %% "scala-xml" % "1.0.6",
+  "org.scalaj" %% "scalaj-http" % "2.4.2",  
+  "org.apache.spark" %% "spark-sql" % "2.4.8"
+)