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HiveQL Kernel

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# HiveQL Kernel

### Requirements

If you are going to connect using kerberos:

` sudo apt-get install python3-dev libsasl2-dev libsasl2-2 libsasl2-modules-gssapi-mit `

### Installation

To install the kernel:

` pip install --upgrade hiveqlKernel jupyter hiveql install --user `

### Connection configuration

Two methods are available to connect to a Hive server:

  • Directly inside the notebook
  • Using a configuration file

If the configuration file is present, everytime you run a new HiveQL kernel it uses it, else you must configure your connection inside the notebook. The configuration in the notebook overwrites the one in the configuration file if present.

#### Configure directly in the notebook cells

Inside a Notebook cell, copy&paste this, change the configuration to match your needs, and run it.

` $$ url=hive://<kerberos-username>@<hive-host>:<hive-port>/<db-name> $$ connect_args={"auth": "KERBEROS", "kerberos_service_name": "hive", "configuration": {"tez.queue.name": "myqueue"}} $$ pool_size=5 $$ max_overflow=10 `

These args are passed to sqlalchemy, who registered pyHive as the ‘hive’ SQL back-end. See [github.com/dropbox/PyHive](https://github.com/dropbox/PyHive/#sqlalchemy).

#### Configure using a configuration file

The HiveQL kernel is looking for the configuration file at ~/.hiveql_kernel.conf by default. You can specify another path using HIVE_KERNEL_CONF_FILE.

The contents must be like this (in json format):

` { "url": "hive://<kerberos-username>@<hive-host>:<hive-port>/<db-name>", "connect_args" : { "auth": "KERBEROS", "kerberos_service_name":"hive", "configuration": {"tez.queue.name": "myqueue"}}, "pool_size": 5, "max_overflow": 10, "default_limit": 20, "display_mode": "be" } `

### Usage

Inside a HiveQL kernel you can type HiveQL directly in the cells and it displays a HTML table with the results.

You also have other options, like changing the default display limit (=20) like this :

` $$ default_limit=50 `

Some hive functions are extended. They allow to filter with some patterns.

` SHOW TABLES <pattern> SHOW DATABASES <pattern> `

### Run tests

` python -m pytest `

Have fun!

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