Spark IoTDB Connecter

version

The versions required for Spark and Java are as follow:

install

mvn clean scala:compile compile install

1. maven dependency

    <dependency>
      <groupId>org.apache.iotdb</groupId>
      <artifactId>spark-iotdb-connector</artifactId>
      <version>0.9.3</version>
    </dependency>

2. spark-shell user guide

spark-shell --jars spark-iotdb-connector-0.9.3.jar,iotdb-jdbc-0.9.3-jar-with-dependencies.jar
import org.apache.iotdb.spark.db._
val df = spark.read.format("org.apache.iotdb.spark.db").option("url","jdbc:iotdb://127.0.0.1:6667/").option("sql","select * from root").load
df.printSchema()
df.show()

if you want to partition your rdd, you can do as following

spark-shell --jars spark-iotdb-connector-0.9.3.jar,iotdb-jdbc-0.9.3-jar-with-dependencies.jar
import org.apache.iotdb.spark.db._
val df = spark.read.format("org.apache.iotdb.spark.db").option("url","jdbc:iotdb://127.0.0.1:6667/").option("sql","select * from root").
                        option("lowerBound", [lower bound of time that you want query(include)]).option("upperBound", [upper bound of time that you want query(include)]).
                        option("numPartition", [the partition number you want]).load
df.printSchema()
df.show()

3. Schema Inference

Take the following TsFile structure as an example: There are three Measurements in the TsFile schema: status, temperature, and hardware. The basic information of these three measurements is as follows:

The existing data in the TsFile is as follows:

The wide(default) table form is as follows:

You can also use narrow table form which as follows: (You can see part 4 about how to use narrow form)

4. Transform between wide and narrow table

from wide to narrow

import org.apache.iotdb.spark.db._
val wide_df = spark.read.format("org.apache.iotdb.spark.db").option("url", "jdbc:iotdb://127.0.0.1:6667/").option("sql", "select * from root where time < 1100 and time > 1000").load
val narrow_df = Transformer.toNarrowForm(spark, wide_df)

from narrow to wide

import org.apache.iotdb.spark.db._
val wide_df = Transformer.toWideForm(spark, narrow_df)

5. Java user guide

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.apache.iotdb.spark.db.*
public class Example {
  public static void main(String[] args) {
    SparkSession spark = SparkSession
        .builder()
        .appName("Build a DataFrame from Scratch")
        .master("local[*]")
        .getOrCreate();
    Dataset<Row> df = spark.read().format("org.apache.iotdb.spark.db")
        .option("url","jdbc:iotdb://127.0.0.1:6667/")
        .option("sql","select * from root").load();
    df.printSchema();
    df.show();
    Dataset<Row> narrowTable = Transformer.toNarrowForm(spark, df)
    narrowTable.show()
  }
}