Spark Insert Data into Hive Tables

Spark (PySpark) DataFrameWriter class provides functions to save data into data file systems and tables in a data catalog (for example Hive). We can use save or saveAsTable (Spark - Save DataFrame to Hive Table) methods to do that. There is also one function named insertInto that can be used to insert the content of the DataFrame into the specified table. The schema of the DataFrame needs to match with the table schema. This article shows you how to insert records into Hive transactional and non-transactional tables.

Prerequisites

If you don't have a Hive instance to work on, you can install one by following these articles:

• Apache Hive 3.1.2 Installation on Linux Guide
• Apache Hive 3.1.2 Installation on Windows 10
  

Insert into Hive tables

The following code snippet insert two new records into a table named test_db.test_table in Hive.

from pyspark.sql import SparkSession

app_name = "PySpark Insert Into Hive Tables"
master = "local"

spark = SparkSession.builder \
    .appName(app_name) \
    .master(master) \
    .enableHiveSupport() \
    .getOrCreate()

spark.sparkContext.setLogLevel("WARN")

# Create a DataFrame
df = spark.sql("select * from test_db.test_table")
df.show()

# Create a new DataFrame
new_data = [[4, 'd'], [5, 'e']]
df_new = spark.createDataFrame(new_data, ['id', 'attr'])
df_new.show()

# Insert into Hive table
df_new.write.insertInto('test_db.test_table', overwrite=False)

Output:

+---+----+
| id|attr|
+---+----+
|  1|   a|
|  2|   b|
|  3|   c|
+---+----+

+---+----+
| id|attr|
+---+----+
|  4|   d|
|  5|   e|
+---+----+

Insert into Hive transactional tables

In article Hive ACID Inserts, Updates and Deletes with ORC, I talks about how Hive transaction tables work with the support of Apache Orc file format.

Unfortunately transactional Hive tables are not supported in Spark right now. [SPARK-15348] Hive ACID - ASF JIRA.