Kinetica manual installation and configuration instructions.
Note
Kinetica can be installed manually on pre-provisioned instances in AWS, Azure, or GCP. For offerings provisioned within cloud environments directly, see Cloud-Ready.
System Requirements
Operating system, hardware, and network requirements to run Kinetica.
Certified OS List
CPU Platform | Linux Distribution | Versions |
---|---|---|
ARM64 | Ubuntu | 20.04 LTS 22.04 LTS |
x86 | RHEL / AlmaLinux / RockyLinux | 8.2+ 9 |
x86 | SUSE | 15.3 |
x86 | Ubuntu | 20.04 LTS 22.04 LTS |
x86-avx512 | RHEL / AlmaLinux / RockyLinux | 8.2+ 9 |
x86-avx512 | Ubuntu | 20.04 LTS |
Minimum Hardware Requirements
Component | Specification |
---|---|
CPU | Two socket based server with at least 8 cores Intel (or compatible) x86-64 or Power PC 8le |
GPU | See GPU Driver below for the list of supported GPUs |
Memory | Minimum 8GB |
Hard Drive | SSD or SATA 7200RPM hard drive with 4X memory capacity |
GPU Driver Matrix
The cards below have been tested in large-scale production environments and provide the best performance for the database.
GPU | Driver | Kinetica Package |
---|---|---|
P4/P40/P100 | 525.X (or higher) | gpudb-cuda-license |
V100 | 525.X (or higher) | gpudb-cuda-license |
T4 | 525.X (or higher) | gpudb-cuda-license |
A10/A40/A100 | 525.X (or higher) | gpudb-cuda-license |
Cluster Preparation
There are some steps that should be followed to set up your network and server configuration before installing Kinetica.
The first step is to collect the IP addresses of the server or servers that will be running Kinetica. If deploying to a cluster, one server must be designated as the head node. This server receives user requests and parcels them out to the other worker nodes of the system. The head node of the cluster (or only node in a single-node system) will also be used for administration of the system, host all services & applications, and as such, will require special handling during the installation process.
Networking Configuration
The Kinetica head node will require a number of ports to be open in order to communicate with its applications & services.
Any worker nodes will need ports opened to communicate with the head node and each other, though this set of ports will be smaller than that of the head node.
Default Ports
The default ports used for communication with KAgent, Kinetica (and between servers, if operating in a cluster), and various important services follow. The Nodes column will list either Head--that the corresponding port only needs to be opened on the head node, or All--that the corresponding port needs to be opened on the head node & worker nodes.
Important
While the table below lists KAgent and the graph server as being on the head node, these features could be kept on machines entirely separate from Kinetica if desired.
Port | Function | Nodes | Usage |
---|---|---|---|
22 | This port is used by KAgent to manage cluster servers. For clusters not managed by KAgent, this will be needed to manage servers directly. | All | Required Internally |
2003 | This port must be open to collect the runtime system statistics. | All | Required Internally |
2004 | This port must be open to collect the runtime system statistics. | All | Required Internally |
4000+N | For installations which have the external text search server enabled and communicating over TCP (rankN.text_index_address = tcp://…), there will be one instance of the text search server listening for each rank on every server in the cluster. Each of these daemons will be listening on a port starting at 4000 on each server and incrementing by one for each additional rank. | All | Optional Internally |
5432 | The listener for PostgreSQL Wire Protocol connections | Head | Optional Externally |
5552 | Host Manager status notification channel | All | Required Internally |
5553 | Host Manager message publishing channel | All | Required Internally |
6555+N | Provides distributed processing of communications between the network and different ranks used in Kinetica. There is one port for each rank running on each server, starting on each server at port 6555 and incrementing by one for each additional rank. | All | Required Internally |
7002 | This port must be open to collect the runtime system statistics. | All | Required Internally |
8000 | The Tomcat listener for the Workbench user interface. | Head | Optional Externally |
8005 | The Tomcat shutdown port for the Kinetica Administration Application (GAdmin) user interface. This port should not be exposed publicly. | Head | Required Internally |
8006 | The Tomcat shutdown port for the KAgent user interface. This port should not be exposed publicly. | Head | Required Internally |
8009 | The Tomcat AJP connector port for the GAdmin user interface. | Head | Required Internally |
8010 | The Tomcat AJP connector port for the KAgent user interface. | Head | Required Internally |
8080 | The Tomcat listener for the GAdmin user interface. | All | Optional Externally |
8081 | The Tomcat listener for the KAgent user interface. | Head | Optional Externally |
8082 | In installations where users need to be authenticated to access the database, a preconfigured HTTPd instance listens on this port, which will authenticate incoming HTTP requests before passing them along to Kinetica. When authorization is required, all requests to Kinetica should be sent here, rather than the standard 9191+ ports. | All | Optional Externally |
8088 | This is the port on which Kinetica Reveal is exposed. For installations that have this feature enabled, it should be exposed to users. | Head | Optional Externally |
8099 | This is the port used for pushing data to the graph server (if enabled) | Head | Required Internally |
8100 | This is the port used for pulling data from the graph server (if enabled) | Head | Required Internally |
8181 | This is the port used to host the system and process stats server | Head | Optional Externally |
8443 | The Tomcat listener for the GAdmin user interface using SSL. | All | Optional Externally |
8444 | This is the port on which Kinetica Reveal is exposed using SSL. For installations that have this feature enabled, it should be exposed to users. | Head | Optional Externally |
8445 | This is the port on which Kinetica Workbench is exposed using SSL. For installations that have this feature enabled, it should be exposed to users. | Head | Optional Externally |
9001 | Database trigger ZMQ publishing server port. Users of database triggers will need the ability to connect to this port to receive data generated via the trigger. | Head | Optional Externally |
9002 | Table monitor publishing server port. Users of database table monitors will need the ability to connect to this port to receive data generated via the table monitor. | Head | Optional Externally |
9003 | Table monitor internal publishing server port. Users of database table monitors on tables that are the targets of multi-head ingest will need to allow worker nodes the ability to connect to this port to receive data generated via the table monitor. | Head | Optional Internally |
9010 | Host collector metrics port. CPU, disk, processes, and other metrics are collected from the /proc filesystem and posted here. | All | Required Internally |
9080 | Port used to host Grafana Loki, a log aggregation system. | All | Required Internally |
9089 | Port used to host the Alert Manager, which manages alerts from Grafana Prometheus and events from Grafana Loki. | All | Required Internally |
9090 | Port used to host Grafana Prometheus, a metric aggregation system. | All | Required Internally |
9091 | Port used to host the Grafana user interface and embeddable metric dashboards in GAdmin. | All | Required Internally, Optional Externally |
9187 | The primary port used for communications with KML. This port should be exposed for any system using the KML API without authorization. | All | Required Internally |
9191+N | The primary port(s) used for public and internal Kinetica communications. There is one port for each rank running on each server, starting on each server at port 9191 and incrementing by one for each additional rank. These should be exposed for any system using the Kinetica APIs without authorization and must be exposed between all servers in the cluster. For installations where users should be authenticated, these ports should NOT be exposed publicly, but still should be exposed between servers within the cluster. | All | Required Internally, Optional Externally |
9300 | Port used to query Host Manager for status | All | Required Internally |
Port Usage Scenarios
Kinetica highly encourages that proper firewalls be maintained and used to protect the database and the network at large. A full tutorial on how to properly set up a firewall is beyond the scope of this document, but the following are some best practices and starting points for more research.
All machines connected to the Internet at large should be protected from intrusion. As shown in the list above, there are no ports which are necessarily required to be accessible from outside of a trusted network, so we recommend only opening ports to the Internet and/or untrusted network(s) which are truly needed based on requirements.
There are some common scenarios which can act as guidelines on which ports should be available.
Connection to the Internet
If Kinetica is running on a server where it will be accessible to the Internet at large, it is our strong suggestion that security and authentication be used and ports 9191+N and 8080 are NOT exposed to the public, if possible. Those ports can potentially allow users to run commands anonymously and unless security is configured to prevent it, any users connecting to them will have full control of the database.
Dependence on Kinetica via the API
For applications in which requests are being made to Kinetica via client APIs that do not use authentication, the 9191+N ports should be made available to the relevant set of servers. For applications using authentication via the bundled version of httpd, port 8082 should be opened. It is possible to have both ports open at the same time in cases where anonymous access is permitted, however the security settings should be carefully set in this case to ensure that anonymous users have the appropriate access limitations.
Additionally, if the API client is using table monitors or triggers, ports 9001, 9002, and/or 9003 should also be opened, as needed.
Reveal
In cases where the GUI interface to Reveal is required, the 8088 port should be made available.
Administration
System administrators may wish to have access to the administrative web interface, in which case port 8080 should be opened, but carefully controlled.
Firewall Settings
RHEL
RHEL uses the firewall-cmd
command or
firewall-config
GUI for configuring the firewall. For example,
the following commands will open up port 8082 publicly:
firewall-cmd --zone=public --add-port=8082/tcp --permanent firewall-cmd --reload
SUSE
SUSE uses the firewall-cmd
command or
firewall-config
GUI for configuring the firewall. For example,
the following commands will open up port 8082 publicly:
firewall-cmd --zone=public --add-port=8082/tcp --permanent firewall-cmd --reload
Ubuntu
Ubuntu comes with a ufw
(Uncomplicated FireWall) command, which
controls the firewall, for example:
sudo ufw allow 8181
System Settings
Each server in the Kinetica cluster should be properly prepared before installing Kinetica. While every system is unique, there are several system parameters which are generally recommended to be set for all nodes in every installation.
Transparent Huge Pages
Transparent Huge Pages are the kernel’s attempt to reduce the overhead of Translation Lookaside Buffer (TLB) lookups by increasing the size of memory pages. This setting is enabled by default, but can lead to sparse memory usage and decreased performance.
sudo sh -c 'echo "never" > /sys/kernel/mm/transparent_hugepage/enabled'
Active Directory
If your environment uses Microsoft Active Directory for authentication and there are security processes running on servers that check for and automatically remove accounts that are not registered in Active Directory, the gpudb user must be added to Active Directory as a Linux-type account prior to installing Kinetica.
Nvidia Drivers
If Nvidia GPUs are present in the target servers, but the drivers have not been installed yet, they should be installed now. See either Install Nvidia Drivers on RHEL or Install Nvidia Drivers on Debian/Ubuntu for details.
Installation
Installation of Kinetica involves the deployment of the installation package, and either a browser-based or console-driven initialization step. Afterwards, passwordless SSH should be configured for ease of management of the system.
The installation process also requires a license key. To receive a license key, contact support at support@kinetica.com.
The Kinetica application needs to be deployed to all servers in the target cluster. Deploy the package using the standard procedures for a local package. Automatically download & install the latest GPU-based Kinetica version using these commands:
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Alternatively, visit the KIN_REPO link below to search for a specific Intel or CUDA version of Kinetica, change KIN_PKG to that file on line 2, and then run the modified commands to download & install that version:
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This installs the package to the directory /opt/gpudb
, creates a group
named gpudb, and two users (gpudb & gpudb_proc) whose home directory
is located at /home/gpudb
. SSH keys are also created to allow
password-less SSH access between servers for the gpudb user when
configured as a cluster. This will also register two services: gpudb &
gpudb_host_manager.
Configuration
Initialization
Once the application has been deployed, choose the configuration method:
- Visual Initialization - for installations where the head node has web browser access
- Console Initialization - for installations without web browser access on the head node
Visual Initialization
The Visual Installer is run through the Kinetica Administration Application (GAdmin) and simplifies the installation of Kinetica.
Browse to the head node, using IP or host name:
http://localhost:8080/
Once you've arrived at the login page, you'll need to change your password and initialize the system using the following steps:
Log into the admin application
- Enter Username: admin
- Enter Password: admin
- Click Login
If a license key has not already been configured, a Product Activation page will be displayed, where the license key is to be entered:
- Enter the license key under Enter License Key
- When complete, click Activate, then confirm the activation
At the Setup Wizard page, configure the system basics:
- Enter the IP Address and number of GPUs (if any) for each server in the cluster
- Optionally, select the Public Head IP Address checkbox and update the address as necessary
- The license key under Configure License Key should already be populated
- When complete, click Save
Important
For additional configuration options, see the Configuration Reference.
Start the system. This will start all Kinetica processes on the head node, and if in a clustered environment, the corresponding processes on the worker nodes.
- Click Admin on the left menu
- Click Start.
See Changing the Administrator Password for instructions on updating the administration account's password.
Skip ahead to Passwordless SSH.
Console Initialization
System configuration is done primarily through the configuration file
/opt/gpudb/core/etc/gpudb.conf
, and while all nodes in a cluster have
this file, only the copy on the head node needs to be modified.
For details on the parameters used in this section, see Configuration Reference.
Important
Only edit the /opt/gpudb/core/etc/gpudb.conf
on the
head node. Editing the file on worker nodes is not supported and may
lead to unexpected results.
Log in to the head node and open
/opt/gpudb/core/etc/gpudb.conf
in an editor.Specify the configuration for each host in the cluster. In this example, there are two servers with three ranks on the first and two ranks on the second:
host0.address = 172.123.45.67 host0.public_address = 172.123.45.67 host0.host_manager_public_url = http://172.123.45.67:9300 host0.ram_limit = 6769400000 host0.gpus = host0.accepts_failover = true host1.address = 172.123.45.68 host1.public_address = 172.123.45.68 host1.host_manager_public_url = http://172.123.45.68:9300 host1.ram_limit = 6769400000 host1.gpus = host1.accepts_failover = true rank0.host = host0 rank1.host = host0 rank2.host = host0 rank3.host = host1 rank4.host = host1
For CUDA builds, the GPUs need to be assigned to ranks. To display the installed GPUs and their status run:
nvidia-smi
If the program is not installed or doesn't run, see Nvidia Drivers.
Once the number of GPUs on each server has been established, enter them into the configuration file by associated rank. In this example, there are two servers with a GPU assigned to each of two ranks per host (none for rank0):
rank0.gpu = 0 # This GPU can be shared with a worker rank, typically rank 1. rank1.taskcalc_gpu = 0 rank2.taskcalc_gpu = 1 rank3.taskcalc_gpu = 0 # On new host, restart at 0 rank4.taskcalc_gpu = 1
For non-CUDA builds, the Numa CPUs need to be assigned to ranks. To display the Numa nodes, run:
numactl -H
Once the number of Numa nodes on each server has been established, enter them into the configuration file by associated rank. In this example, there are two servers with a Numa node assigned to each of two ranks per host (none for rank0):
rank0.numa_node = # Preferring a node for the head node HTTP server is often not necessary. rank1.base_numa_node = 0 rank2.base_numa_node = 1 rank3.base_numa_node = 0 # On new host, restart at 0 rank4.base_numa_node = 1 rank1.data_numa_node = 0 rank2.data_numa_node = 1 rank3.data_numa_node = 0 # On new host, restart at 0 rank4.data_numa_node = 1
Set the license key:
license_key = ...
Optionally, enable the text search capability:
enable_text_search = true
Caution!
Text search is required if KML usage is desired.
Determine the directory in which database files will be stored. It should meet the following criteria:
- Available disk space that is 4x memory
- Writable by the gpudb user
- Consist of raided SSDs
- Not be part of a network share or NFS mount
Enter the database file directory path into the configuration:
persist_directory = /opt/gpudb/persist
Important
For additional configuration options, see the Configuration Reference.
Save the file.
Start the gpudb service. This will start all Kinetica processes on the head node, and if in a clustered environment, processes on the worker nodes:
service gpudb start
Log into the admin application and change the administration account's default password.
Passwordless SSH
If Kinetica is installed in a clustered environment, configuring passwordless SSH will make management considerably easier. Run the following command on the head node to set up passwordless SSH between the head node and the worker nodes for the gpudb users created during deployment:
sudo /opt/gpudb/core/bin/gpudb_hosts_ssh_copy_id.sh
If necessary, you can copy SSH public keys for non-gpudb users to all the hosts in a cluster (made available with gpudb_hosts_addresses.sh) using the ssh-copy-id tool that is part of OpenSSH:
ssh-copy-id -i ~/.ssh/<public_key_name> <user>@<hostname>
Starting Kinetica
See Managing All Services for the command-line reference for starting and stopping Kinetica services.
Validation
To validate that Kinetica has been installed and started properly, you can perform the following tests.
Curl Test
To ensure that Kinetica has started (you may have to wait a moment while the system initializes), you can run curl on the head node to check if the server is responding and port is available with respect to any running firewalls:
$ curl localhost:9191 Kinetica is running!
API Test
You can also run a test to ensure that the API is responding properly. There is an admin simulator project in Python provided with the Python API, which pulls statistics from the Kinetica instance. Running this on the head node, passing in the appropriate <username> & <password>, you should see:
$ /opt/gpudb/bin/gpudb_python /opt/gpudb/kitools/gadmin_sim.py -u <username> -p <password> --table --summary +-----------------+--------------------------------+----------------------+----------------------+-------+ | Schema | Table/View | Records | Type ID | TTL | +=================+================================+======================+======================+=======+ | SYSTEM | <ALL TABLES/VIEWS> | 1 | | | | SYSTEM | ITER | 1 | UNSET_TYPE_ID | -1 | +-----------------+--------------------------------+----------------------+----------------------+-------+ +---------------------------+----------------------+ | Object Type | Count | +===========================+======================+ | Schemas | 1 | | Tables & Views | 1 | | Records | 1 | | Records + Track Elements | 1 | +---------------------------+----------------------+
GAdmin Status Test
The administrative interface itself can be used to validate that the system is functioning properly. Simply log into GAdmin. Browse to Dashboard to view the status of the overall system and Ranks to view the status breakdown by rank.
Ingest/Read Test
After verifying Kinetica has started and its components work, you should confirm ingesting and reading data works as expected.
- Navigate to the Demo tab on the Cluster page.
- Click Load Sample Data under the NYC Taxi section, then click Load to confirm.
- Once the data is finished loading, click View Loaded Data. The data should be available in the nyctaxi table located in the demo schema.
If Reveal is enabled:
Navigate to:
http://<head-node-ip-address>:8088/
Log into Reveal and change the administration account's default password.
Click NYC Taxi under Dashboards. The default NYC Taxi dashboard should load.
Core Utilities
Kinetica comes packaged with many helpful server and support executables that can be found in /opt/gpudb/core/bin/ and /opt/gpudb/bin. Note that any of the gpudb_hosts_*.sh scripts will operate on the hosts specified in gpudb.conf. Run any of the following with the -h option for usage information.
Important
For most of the utilities that use passwordless SSH, an AWS PEM file can be specified instead using the -i option (with the exception being the gpudb_hosts_persist_* scripts). If passwordless SSH is not setup and no PEM file is specified, you will be prompted for a password on each host.
Environment Configuration and Tools
Some of the most commonly used and important utilities are also available in the /opt/gpudb/bin directory.
Note
This directory also contains the KI Tools suite
Utility / Script | Uses Passwordless SSH | Description |
---|---|---|
gpudb_alter_password | No | Script to change a given user's password |
gpudb_env | No | Utility to run a program and its given arguments after setting the PATH, LD_LIBRARY_PATH, PYTHON_PATH, and others to the appropriate /opt/gpudb/ directories. Use this script or /opt/gpudb/bin/gpudb_python to correctly setup the environment to run Kinetica's packaged Python version. You can also run source /opt/gpudb/core/bin/gpudb_env.sh to have the current environment updated. |
gpudb_pip | Yes | Script to run Kinetica's packaged pip version. Runs on all hosts. This can be used in place of pip, e.g., /opt/gpudb/bin/gpudb_pip install gpudb |
gpudb_python | No | Script to correctly setup the environment to run Kinetica's packaged Python version. This can be used in place of the python command, e.g., /opt/gpubd/bin/gpudb_python my_python_file.py |
gpudb_udf_distribute_thirdparty | No | Utility to mirror the local /opt/gpudb/udf/thirdparty to remote hosts. Creates a dated backup on the remote host before copying |
Helper Scripts
Additional helper scripts and utilities are available in /opt/gpudb/core/bin.
Utility / Script | Uses Passwordless SSH | Description |
---|---|---|
gpudb | No | Run as gpudb user or root. The Kinetica system start/restart/stop/status script |
gpudb_alter_password.py | No | Script to change a given user's password |
gpudb_cluster_cuda | No | Server executable for CUDA clusters. Displays version and configuration information. This should only be run by the gpudb executable (see above). |
gpudb_cluster_intel | No | Server executable for Intel clusters. Displays version and configuration information. This should only be run by the gpudb executable (see above). |
gpudb_conf_parser.py | No | Run using /opt/gpudb/bin/gpudb_python. Utility for parsing the /opt/gpudb/core/etc/gpudb.conf file and printing the settings and values. |
gpudb_config_compare.py | No | Script to compare two configuration files: a "modified" configuration file and a "baseline" configuration file. The script can also merge the files after outputting the diff. The merged file will use the "modified" file's settings values if the "modified" configuration settings match the "baseline" configuration settings; if a setting value is present in the "modified" file but not in the "baseline" file, the "baseline" setting value will be used. Supports .ini, .conf, .config, .py, and .json files. |
gpudb_decrypt.sh | No | Utility for decrypting text encrypted by gpudb_encrypt.sh. See Obfuscating Plain-Text Passwords for details. |
gpudb_disk_mount_azure.sh | No | Utility used for attaching and detaching data volumes for Kinetica clusters running in Microsoft Azure. |
gpudb_encrypt.sh | No | Utility for encrypting text. See Obfuscating Plain-Text Passwords for details. |
gpudb_env.sh | No | Utility to run a program and its given arguments after setting the PATH, LD_LIBRARY_PATH, PYTHON_PATH, and others to the appropriate /opt/gpudb/ directories. Use this script or /opt/gpudb/bin/gpudb_python to correctly setup the environment to setup the environment to run Kinetica's packaged Python version. You can also run source /opt/gpudb/core/bin/gpudb_env.sh to have the current environment updated. |
gpudb_file_integrity_check.py | No | Utility to test the consistency of the /opt/gpudb/persist directory |
gpudb_generate_key.sh | No | Utility for generating an encryption key. See Obfuscating Plain-Text Passwords for details. |
gpudb_host_manager | No | The host daemon process that starts and manages any Kinetica processes. |
gpudb_hosts_addresses.sh | Yes | Prints all the unique hostnames (or IPs) specified in gpudb.conf |
gpudb_hosts_diff_file.sh | Yes | Run as gpudb user or root. Utility to diff a given file from the current machine to the specified destination file on one or more hosts |
gpudb_hosts_logfile_cleanup.sh | Yes | Run as gpudb user or root. Script to delete old log files and optionally keep the last n logs |
gpudb_hosts_persist_clear.sh | Yes | Run as gpudb user or root. Script to clear the database persist files (location specified in gpudb.conf) Important: Only run this while the database is stopped. |
gpudb_hosts_rsync_to.sh | Yes | Run as gpudb user. Script to copy files from this server to the remove servers using rsync |
gpudb_hosts_ssh_copy_id.sh | Yes | Run as gpudb user or root. Script to distribute the gpudb user's public SSH keys to the other hosts defined in gpudb.conf to allow password-less SSH. This script should only be run from the head node. Important: This script should be re-run after changing the host configuration to redistribute the keys |
gpudb_hosts_ssh_execute.sh | Yes | Run as gpudb user or root. Script to execute a program with arguments on all hosts specified in gpudb.conf, e.g., ./gpudb_hosts_ssh_execute.sh "ps aux" or ./gpudb_hosts_ssh_execute.sh "hostname" |
gpudb_hosts_ssh_setup_passwordless.sh | Yes | Script to add an authorized SSH key for a given user across a set of hosts. |
gpudb_keygen | No | Executable to generate and print a machine key. You can use the key to obtain a license from support@kinetica.com |
gpudb_log_plot_job_completed_time.sh | No | Plots job completion time statistics using gnuplot |
gpudb_machine_info.sh | No | Script to print OS config information that affects performance as well as suggestions to improve performance |
gpudb_migrate_persistence.py | No | Utility to migrate data from a local persist directory into the database |
gpudb_nvidia_setup.sh | No | Utility to configure the Nvidia GPU devices for best performance or restore defaults. Root permission is required to change values. Utility reports informational settings and permission errors when run as user |
gpudb_open_files.sh | No | Script to print the files currently open by the database |
gpudb_process_monitor.py | No | Script to check a process list against a matching regular expression and print a log to stdout when the process is started or stopped. The script can also run a program, send emails, and/or SNMP alerts when the process starts or stops. The script can be configured using a configuration file, but note that some settings can be overridden from the command line. |
gpudb_sysinfo.sh | No | More information when run as root. Script to print a variety of information about the system and hardware for debugging. You can also make a .tgz file of the output. Rerun this program as needed to keep records of the system. Use a visual diff program to compare two or more system catalogs |
gpudb_udf_distribute_thirdparty.sh | Yes | Utility to mirror the local /opt/gpudb/udf/thirdparty to remote hosts. Creates a dated backup on the remote host before copying |
gpudb_useradd.sh | No | Script to create the gpudb:gpudb and gpudb_proc:gpudb_proc user:groups and SSH id. This script can be rerun as needed to restore the user:groups and ssh config. Be sure to rerun (on the head node only) gpudb_hosts_ssh_copy_id.sh to redistribute the SSH keys if desired whenever the SSH keys are changed |
Logging
The best way to troubleshoot any issues is by searching through the available logs. For more information on changing the format of the logs, see Custom Logging. Each component in Kinetica has its own log, the location of which is detailed below:
Component | Log Location |
---|---|
Kinetica Machine Learning (KML) | /opt/gpudb/kml/logs/ |
GAdmin (Tomcat) | /opt/gpudb/tomcat/logs/ |
Graph Server | /opt/gpudb/graph/logs/ |
KAgent (Service) | /opt/gpudb/kagent/logs/ |
KAgent (UI) | /opt/gpudb/kagent/ui/logs/ |
Kinetica system logs | /opt/gpudb/core/logs/ |
Reveal | /opt/gpudb/connector/reveal/logs/ |
SQL Engine | /opt/gpudb/sql/logs/ |
Stats Server | /opt/gpudb/kagent/stats/logs/ |
Text Server | /opt/gpudb/text/logs/ |
Uninstallation
Should you need to uninstall Kinetica, you'll need to shut down the system, remove the package, and remove related files, directories, & user accounts.
- Stop the system
- Remove the Kinetica package from your
machine:RHEL
1
sudo yum remove gpudb-<gpuhardware>-<licensetype>
Ubuntu1
sudo apt remove gpudb-<gpuhardware>-<licensetype>
SUSE1
sudo zypper remove gpudb-<gpuhardware>-<licensetype>
- Optionally, remove the Kinetica Machine Learning (KML) package from your
machine:RHEL
1
sudo yum remove kinetica-ml
Ubuntu1
sudo apt remove kinetica-ml
SUSE1
sudo zypper remove kinetica-ml
- Remove any user-defined persist directories (these directories are set
in
/opt/gpudb/core/etc/gpudb.conf
) - Clean-up all Kinetica
artifacts:
1
sudo rm -rf /opt/gpudb
- Remove the
gpudb
&gpudb_proc
users from the machine:RHEL1 2
sudo userdel -r gpudb sudo userdel -r gpudb_proc
Ubuntu1 2
sudo deluser --remove-home gpudb sudo deluser --remove-home gpudb_proc
SUSE1 2
sudo userdel -r gpudb sudo userdel -r gpudb_proc
- Remove the
gpudb
group from the machine:1
groupdel gpudb