How to integrate Apache Spark with MySQL for reading database tables as a spark dataframe? [closed]

Answer 1

public static void main(String[] args) {
    Map<String, String> options = new HashMap<String, String>();
    options.put("url","jdbc:postgresql://<DBURL>:<PORT>/<Database>?user=<UserName>&password=<Password>");
    options.put("dbtable", "<TableName>");
    JavaSparkContext sc = new JavaSparkContext(new SparkConf().setAppName("DBConnection").setMaster("local[*]"));
    SQLContext sqlContext = new org.apache.spark.sql.SQLContext(sc);
    // DataFrame jdbcDF = sqlContext.load("jdbc", options).cache();
    DataFrame jdbcDF = sqlContext.jdbc(options.get("url"),options.get("dbtable"));
    System.out.println("Data------------------->" + jdbcDF.toJSON().first());
    Row[] rows = jdbcDF.collect();
    System.out.println("Without Filter \n ------------------------------------------------- ");
    for (Row row2 : rows) {
        System.out.println(row2.toString());
    }
    System.out.println("Filter Data\n ------------------------------------------------- ");
    jdbcDF = jdbcDF.select("agency_id","route_id").where(jdbcDF.col("route_id").$less$eq(3));
    rows = jdbcDF.collect();
    for (Row row2 : rows) {
        System.out.println(row2.toString());
    }
}

Answer 2

From pySpark, it work for me :

dataframe_mysql = mySqlContext.read.format("jdbc").options(
    url="jdbc:mysql://localhost:3306/my_bd_name",
    driver = "com.mysql.jdbc.Driver",
    dbtable = "my_tablename",
    user="root",
    password="root").load()

Answer 3

For Scala if you use the sbt this will also work.

In your build.sbt file:

libraryDependencies ++= Seq(
    "org.apache.spark" %% "spark-core" % "1.6.2",
    "org.apache.spark" %% "spark-sql" % "1.6.2",
    "org.apache.spark" %% "spark-mllib" % "1.6.2",
    "mysql" % "mysql-connector-java" % "5.1.12"
)

Then you just need to declare your usage of the driver.

Class.forName("com.mysql.jdbc.Driver").newInstance

val conf = new SparkConf().setAppName("MY_APP_NAME").setMaster("MASTER")

val sc = new SparkContext(conf)

val sqlContext = new SQLContext(sc)

val data = sqlContext.read
.format("jdbc")
.option("url", "jdbc:mysql://<HOST>:3306/<database>")
.option("user", <USERNAME>)
.option("password", <PASSWORD>)
.option("dbtable", "MYSQL_QUERY")
.load()

Answer 4

Based on this infoobjects article try the following (assuming Java or Scala, not sure how this would work with python):

• add the mysql-connector-java to the path of your spark cluster
• initialize the driver: Class.forName("com.mysql.jdbc.Driver")
• create a JdbcRDD data source:

---

val myRDD = new JdbcRDD( sc, () => 
                               DriverManager.getConnection(url,username,password),
                        "select first_name,last_name,gender from person limit ?, ?",
                        1,//lower bound
                        5,//upper bound
                        2,//number of partitions
                        r =>
                          r.getString("last_name") + ", " + r.getString("first_name"))

Answer 5

Using Scala, this worked for me : Use the commands below:

sudo -u root spark-shell --jars /mnt/resource/lokeshtest/guava-12.0.1.jar,/mnt/resource/lokeshtest/hadoop-aws-2.6.0.jar,/mnt/resource/lokeshtest/aws-java-sdk-1.7.3.jar,/mnt/resource/lokeshtest/mysql-connector-java-5.1.38/mysql-connector-java-5.1.38/mysql-connector-java-5.1.38-bin.jar --packages com.databricks:spark-csv_2.10:1.2.0

import org.apache.spark.sql.SQLContext

val sqlcontext = new org.apache.spark.sql.SQLContext(sc)

val dataframe_mysql = sqlcontext.read.format("jdbc").option("url", "jdbc:mysql://Public_IP:3306/DB_NAME").option("driver", "com.mysql.jdbc.Driver").option("dbtable", "tblage").option("user", "sqluser").option("password", "sqluser").load()

dataframe_mysql.show()

Answer 6

With spark 2.0.x,you can use DataFrameReader and DataFrameWriter. Use SparkSession.read to access DataFrameReader and use Dataset.write to access DataFrameWriter.

Suppose using spark-shell.

read example

val prop=new java.util.Properties()
prop.put("user","username")
prop.put("password","yourpassword")
val url="jdbc:mysql://host:port/db_name"

val df=spark.read.jdbc(url,"table_name",prop) 
df.show()

read example 2

val jdbcDF = spark.read
  .format("jdbc")
  .option("url", "jdbc:mysql:dbserver")
  .option("dbtable", "schema.tablename")
  .option("user", "username")
  .option("password", "password")
  .load()

from spark doc

read example3

If you want to read data from a query result rather than a table.

val sql="""select * from db.your_table where id>1"""
val jdbcDF = spark.read
  .format("jdbc")
  .option("url", "jdbc:mysql:dbserver")
  .option("dbtable",  s"( $sql ) t")
  .option("user", "username")
  .option("password", "password")
  .load()

write example

import org.apache.spark.sql.SaveMode

val prop=new java.util.Properties()
prop.put("user","username")
prop.put("password","yourpassword")
val url="jdbc:mysql://host:port/db_name"
//df is a dataframe contains the data which you want to write.
df.write.mode(SaveMode.Append).jdbc(url,"table_name",prop)

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