How to connect Spark SQL to remote Hive metastore (via thrift protocol) with no hive-site.xml?
For Spark 1.x, you can set with :
System.setProperty("hive.metastore.uris", "thrift://METASTORE:9083");
final SparkConf conf = new SparkConf();
SparkContext sc = new SparkContext(conf);
HiveContext hiveContext = new HiveContext(sc);
Or
final SparkConf conf = new SparkConf();
SparkContext sc = new SparkContext(conf);
HiveContext hiveContext = new HiveContext(sc);
hiveContext.setConf("hive.metastore.uris", "thrift://METASTORE:9083");
Update If your Hive is Kerberized :
Try setting these before creating the HiveContext :
System.setProperty("hive.metastore.sasl.enabled", "true");
System.setProperty("hive.security.authorization.enabled", "false");
System.setProperty("hive.metastore.kerberos.principal", hivePrincipal);
System.setProperty("hive.metastore.execute.setugi", "true");
In spark 2.0.+ it should look something like that:
Don't forget to replace the "hive.metastore.uris" with yours. This assume that you have a hive metastore service started already (not a hiveserver).
val spark = SparkSession
.builder()
.appName("interfacing spark sql to hive metastore without configuration file")
.config("hive.metastore.uris", "thrift://localhost:9083") // replace with your hivemetastore service's thrift url
.enableHiveSupport() // don't forget to enable hive support
.getOrCreate()
import spark.implicits._
import spark.sql
// create an arbitrary frame
val frame = Seq(("one", 1), ("two", 2), ("three", 3)).toDF("word", "count")
// see the frame created
frame.show()
/**
* +-----+-----+
* | word|count|
* +-----+-----+
* | one| 1|
* | two| 2|
* |three| 3|
* +-----+-----+
*/
// write the frame
frame.write.mode("overwrite").saveAsTable("t4")
I too faced same problem, but resolved. Just follow this steps in Spark 2.0 Version
Step1: Copy hive-site.xml file from Hive conf folder to spark conf.
Step 2: edit spark-env.sh file and configure your mysql driver. (If you are using Mysql as a hive metastore.)
Or add MySQL drivers to Maven/SBT (If using those)
Step3: When you are creating spark session add enableHiveSupport()
val spark = SparkSession.builder.master("local").appName("testing").enableHiveSupport().getOrCreate()
Sample code:
package sparkSQL
/**
* Created by venuk on 7/12/16.
*/
import org.apache.spark.sql.SparkSession
object hivetable {
def main(args: Array[String]): Unit = {
val spark = SparkSession.builder.master("local[*]").appName("hivetable").enableHiveSupport().getOrCreate()
spark.sql("create table hivetab (name string, age int, location string) row format delimited fields terminated by ',' stored as textfile")
spark.sql("load data local inpath '/home/hadoop/Desktop/asl' into table hivetab").show()
val x = spark.sql("select * from hivetab")
x.write.saveAsTable("hivetab")
}
}
Output: