Spark SQL Example



Spark SQL Example

This example demonstrates how to use sqlContext.sql to create and load a table and select rows from the table into a DataFrame. The next steps use the DataFrame API to filter the rows for salaries greater than 150,000 and show the resulting DataFrame.

1. At the command-line, copy the Hue sample_07 data to HDFS:

   $ hdfs dfs -put HUE_HOME/apps/beeswax/data/sample_07.csv /user/hdfs

   where HUE_HOME defaults to /opt/cloudera/parcels/CDH/lib/hue (parcel installation) or /usr/lib/hue (package installation).
2. Start spark-shell:

   $ spark-shell

3. Create a Hive table:

   scala> sqlContext.sql("CREATE TABLE sample_07 (code string,description string,total_emp int,salary int) ROW FORMAT DELIMITED FIELDS TERMINATED BY '	' STORED AS TextFile")

4. Load data from HDFS into the table:

   scala> sqlContext.sql("LOAD DATA INPATH '/user/hdfs/sample_07.csv' OVERWRITE INTO TABLE sample_07")

5. Create a DataFrame containing the contents of the sample_07 table:

   scala> val df = sqlContext.sql("SELECT * from sample_07")

6. Show all rows with salary greater than 150,000:

   scala> df.filter(df("salary") > 150000).show()

   The output should be:

   +-------+--------------------+---------+------+
   |   code|         description|total_emp|salary|
   +-------+--------------------+---------+------+
   |11-1011|    Chief executives|   299160|151370|
   |29-1022|Oral and maxillof...|     5040|178440|
   |29-1023|       Orthodontists|     5350|185340|
   |29-1024|     Prosthodontists|      380|169360|
   |29-1061|   Anesthesiologists|    31030|192780|
   |29-1062|Family and genera...|   113250|153640|
   |29-1063| Internists, general|    46260|167270|
   |29-1064|Obstetricians and...|    21340|183600|
   |29-1067|            Surgeons|    50260|191410|
   |29-1069|Physicians and su...|   237400|155150|
   +-------+--------------------+---------+------+