Create a Sqoop import command

You create a single Sqoop import command that imports data from diverse data sources, such as a relational database on a different network, into Hive using Apache Sqoop.

You enter the Sqoop import command on the command line of your Hive cluster to import data from a data source into HDFS and Hive. The import can include the following information, for example:

Database connection information: database URI, database name, and connection protocol, such as jdbc:mysql:
The data to import
Parallel processing directives for fast data transfer
Destination for imported data

Sqoop is tested to work with Connector/J 5.1. If you have upgraded to Connector/J 8.0, and want to use the zeroDateTimeBehavior property to handle values of '0000-00-00\' in DATE columns, explicitly specify zeroDateTimeBehavior=CONVERT_TO_NULL in the connection string. For example,

--connect jdbc:mysql://<MySQL
            host>/<DB>?zeroDateTimeBehavior=CONVERT_TO_NULL

Create an import command that specifies the Sqoop connection to the RDBMS.
- To enter a password for the data source on the command line, use the -P option in the connection string.
- To specify a file where the password is stored, use the --password-file option.
Password on command line:
```
sqoop import --connect jdbc:mysql://db.foo.com:3306/bar \
<data to import> \
--username <username> \
-P
```
Specify password file:
```
sqoop import --connect jdbc:mysql://db.foo.com:3306/bar \
--table EMPLOYEES \
--username <username> \
--password-file ${user.home}/.password 
```

Specify the data to import in the command.

Import an entire table.
Import a subset of the columns.
Import data using a free-form query.

Entire table:

sqoop import \
--connect jdbc:mysql://db.foo.com:3306/bar \
--table EMPLOYEES

Subset of columns:

sqoop import 
--connect jdbc:mysql://db.foo.com:3306/bar \
--table EMPLOYEES \
--columns "employee_id,first_name,last_name,job_title"

Free-form query to import the latest data:

sqoop import \
--connect jdbc:mysql://db.foo.com:3306/bar \
--table EMPLOYEES \
--where "start_date > '2018-01-01'"

Optionally, specify write parallelism in the import statement to execute a number of map tasks in parallel:
- Set mappers: If the source table has a primary key, explicitly set the number of mappers using --num-mappers.
- Split by: If primary keys are not evenly distributed, provide a split key using --split-by
- Sequential: If you do not have a primary key or split key, import data sequentially using --num-mappers 1 or --autoreset-to-one-mapper in query.
- Set mappers:
```
sqoop import --connect jdbc:mysql://db.foo.com:3306/bar \
 --table EMPLOYEES \
 --num-mappers 8 \
```
- Split by:
```
sqoop import --connect jdbc:mysql://db.foo.com:3306/bar \
 --table EMPLOYEES \
 --split-by dept_id
```
- Setting mappers evenly splits the primary key range of the source table.
- Split by evenly splits the data using the split key instead of a primary key.
Specify importing the data into Hive using Hive default delimiters --hive-import.
Specify the Hive destination of the data.
- If you think the table does not already exist in Hive, name the database and table, and use the --create-hive-table option.
- If you want to insert the imported data into an existing Hive external table, name the database and table, but do not use the --create-hive-table option.
This command imports the MySQL EMPLOYEES table to a new Hive table named in the warehouse.
```
sqoop import --connect jdbc:mysql://db.foo.com:3306/corp \
--table EMPLOYEES \
--hive-import \
--create-hive-table \
--hive-database 'mydb' \
--hive-table 'newtable'
```
This command imports the MySQL EMPLOYEES table to an external table in HDFS.
```
sqoop import --connect jdbc:mysql://db.foo.com:3306/corp \
--table EMPLOYEES \
--hive-import \
--hive-database 'mydb' \
--hive-table 'myexternaltable'
```
Specify the database and table names, enclosed in single quotation marks, on separate lines (recommended) as shown above. Alternatively specify the database and table names on one line, and enclose the database and table names in backticks.

--hive-table `mydb`.`myexternaltable`

Due to the Hive-16907 bug fix, Hive rejects `db.table` in SQL queries. A dot (.) is no longer allowed in table names. You need to change queries that use such references to prevent Hive from interpreting the entire db.table string as the table name.