I use the plain and old Junit
Spark batch example:
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.sql.SQLContext
import org.junit.AfterClass
import org.junit.Assert.assertEquals
import org.junit.BeforeClass
import org.junit.Test
object TestMyCode {
var sc: SparkContext = null
@BeforeClass
def setup(): Unit = {
val sparkConf = new SparkConf()
.setAppName("Test Spark")
.setMaster("local[*]")
sc = new SparkContext(sparkConf)
}
@AfterClass
def cleanup(): Unit = {
sc.stop()
}
}
class TestMyCode {
@Test
def testSaveNumbersToExtractor(): Unit = {
val sql = new SQLContext(TestDataframeToTableau.sc)
import sql.implicits._
val numList = List(1, 2, 3, 4, 5)
val df = TestDataframeToTableau.sc.parallelize(numList).toDF
val numDf = df.select(df("_1").alias("num"))
assertEquals(5, numDf.count)
}
}
On Wed, Mar 2, 2016 at 2:54 PM, SRK [via Apache Spark User List] <
ml-node+s1001560n26380...@n3.nabble.com> wrote:
> Hi,
>
> What is a good unit testing framework for Spark batch/streaming jobs? I
> have core spark, spark sql with dataframes and streaming api getting used.
> Any good framework to cover unit tests for these APIs?
>
> Thanks!
>
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--
Ricardo Paiva
Big Data / Semântica
2483-6432
*globo.com* <http://www.globo.com>
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