Spark IoTDB连接器

mvn clean scala:compile compile install

1. Maven依赖

2. Spark-shell用户指南

spark-shell --jars spark-iotdb-connector-0.11.1.jar,iotdb-jdbc-0.11.1-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()

3. 模式推断

TsFile中的现有数据如下：

你还可以使用窄表形式，如下所示：（您可以参阅第4部分，了解如何使用窄表形式）

4. 在宽和窄表之间转换

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)

5. Java用户指南

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) {
        .builder()
        .appName("Build a DataFrame from Scratch")
        .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()