Overview

This chapter explains the prerequisite and precautions before installing Tibero client, considerations after installation and Tibero client installation methods on Linux.

Document Organization

The guide contains 2 chapters.

Uninstalling manually

Run $TB_HOME/.installation/Tibero_Uninstaller, which is supported for all platforms.

Download documents

Installation in manual mode

1. Prepare the installation file(tar.gz) and license file(license.xml).

Overview

The current enterprise business rapidly expands with the explosive increase of data and the advent of a variety of new environments and platforms. This new business environment requires more flexible and efficient data services, information handling, and data management functions.

Tibero is an enterprise database management system that supports building a database infrastructure on which enterprise business is implemented and provides high performance, high availability, and scalability.

To address limitations of existing databases, Tibero implemented its proprietary Tibero thread architecture. It also uses limited system resources such as CPU and memory efficiently, guarantees high performance and reliability, and provides a convenient development environment and management features.

Tibero, from its very earliest version, has been developed to handle a large number of users and large amounts of data while ensuring reliability and compatibility.

Preparations before installing

1. Check available disk space

Overview

This document is intended for all database users who want to install or uninstall Tibero®(Tibero).

Required Knowledge

• Database

• RDBMS

• OSs and system environments

• Unix (including Linux)

Document Organization

The guide contains 6 chapters and 7 appendix.

Appendix

Overview

This guide is intended for database administrators (hereafter DBA) who want to use the Hadoop Connector in Tibero.

Required Knowledge

• Databases

• RDBMS

• Operating systems and system environments

• UNIX and Linux

Document Organization

The guide contains 2 chapters.

Installation

In Unix (Linux), multiple instances from different databases can be simultaneously installed.

These instances can share a single Tibero binary execution file and a Tibero license file, but their TB_SID and configuration file (.tip) must be separately configured.

AIX

The method for mounting a CD-ROM in AIX is as follows:

1. Log in as the root user.

Overview

This chapter explains the prerequisite and precautions before installing Tibero client, considerations after installation and Tibero client installation methods on Windows.

External Procedure is the functions users write in an external language (any programming language Tibero supports) such as C or Java programming languages. The procedure is treated as a PSM function (or procedure) in Tibero. Users can invoke the procedures when they want to use any user defined library. They can also get the processed result.

The external procedures in Tibero are used:

• To issue an event in the DBMS using email, SMS, and network.

• To compress a file depending on the size of the entire disk or the file, or to move it to an external disk.

Hadoop is an open-source framework solution from Apache Software Foundation to facilitate storage, distribution, and parallel processing of large amounts of data.

Hadoop includes the following software stacks.

• HDFS(Hadoop Distributed File System) A distributed file system that provides failure recovery and high availability through data block redundancy in a distributed file system.

• MapReduce A distributed programming framework that automatically performs distributed parallel processing on tasks that are divided into Map and Reduce. It supports parallel and distributed processing using resources from multiple nodes and failure recovery function.

In summary, Hadoop is a system aimed at mass storage and fast processing of data.

The number of businesses using Hadoop is increasing rapidly as the amount of data is growing exponentially. However, Hadoop requires a MapReduce program for data processing which creates high programming burden to create various queries needed for data analysis. It lacks an interactive SQL interface with immediate feedback causing inconvenience in having to write code to achieve the desired results.

There are also many cases that require multiple types of data sources to store various data formats.

In such cases, unstructured data is stored in HDFS, and structured data in the existing RDBMS. Combining heterogeneous data sources to analyze legacy database and big data together dramatically increases data processing complexity.

Key Features

Tibero Hadoop Connector is a solution that satisfies big data processing requirements, and the need for heterogeneous data source integration and convenient interface.

The following Tibero Hadoop Connector features are provided to supplement Hadoop.

• Provides Extern Table interface to process data stored in HDFS with data in RDBMS tables.

• External Table interface reduces data migration inconvenience.

• Supports all query functions of Tibero.

• Supports data integration functions such as table joins between HBase and Tibero tables.

Data in Hadoop can be combined with data in Tibero in a query using Ansi-SQL. The access interface between Tibero and Hadoop HDFS is unified in SQL, which reduces the burden of using heterogeneous data sources. Using SQL to perform various queries according to the fast changing data analysis needs facilitates a fast data analysis process.

Tibero Hadoop Connector uses the External Table function to access data so that queries can be performed on various data formats as with structured data. Various functions including query processing functions provided by Tibero InfiniData can also be used with data in Hadoop.

In summary, Tibero Hadoop Connector enables easy integrated analysis of data in Hadoop and RDBMS. Such agile big data analysis functionality can help to quickly respond to the rapidly changing business environment.

Supported Hadoop Versions

Tibero HDFS Connector only supports Linux. HDFS Connector supports Hadoop 1.2.X versions.

Overview

This document is intended for database administrators (DBA) and application developers who want to use the In-Memory Column Store (IMCS) function provided in Tibero

Required Knowledge

• Database

• RDBMS

• SQL

Document Organization

This guide consists of 4 chapters.

Backup

The following is an example of backing up all data of a TAS disk space to the "/backupdir" directory by using the tbrmgr command.

[Example 1] Backing Up TAS Disk Space Data

Recovery

The following is an example of recovering data of a TAS disk space with the backup copy in the "/backupdir" directory by using the tbrmgr command.

[Example 2] Recovering TAS Disk Space Data

HDFS External Table Creation

The syntax for creating an external table using the HDFS Connector is the same as the general syntax for creating an external table.

In the previous syntax, Port is optional and 8020 is its default value.

The following is an example of defining an external table using the HDFS Connector.

The previous example creates three HDFS files for the external table. The host name of the HDFS Namenode is 'hadoop_name', and the port number defaults to 8020. Next, it reads the three files, 'f0.txt', 'f1.txt', and 'f2.txt', from the '/user/tibero' directory below HDFS.

Preparations before installing

1. Check available disk space

IMCS in TAC

When using IMCS in Tibero Active Cluster (TAC), every running instance has its own IMCS area. By default, objects populated in a TAC environment are distributed across all nodes in the cluster.

In Tibero, the INMEMORY_SIZE parameter for every TAC node must be set to an equal value.

Overview

This guide is intended for database administrators (DBA) who intend to use Tibero to build and maintain spatial reference systems and developers who develop applications using the systems.

Features

Available only in the following operating systems:

Linux, AIX 64-bit, HP-UX 64-bit, and Solaris 5.10 64-bit.

The shared memory in Tibero is divided into fixed memory and shared pool memory as follows:

• Fixed Memory Its size is fixed based on a parameter value set at database startup.

  – Buffer cache (database buffer)

  – Log buffer

  – Others: space for global variables and managing working threads and session information.

• Shared Pool Memory It is dynamically allocated during database operation.

  – DD cache

  – PP cache (library cache)

  – Others

Considerations

Consider the following when calculating the size of the shared memory.

• The size of the shared memory cannot be increased dynamically while the database is running.

• The size of the shared memory must be determined properly based on the usage patterns of the buffer cache and shared pool.

- Buffer Cache

• Determine the size according to the Buffer Cache Hit rate in TPR after executing major workloads.

• If the hit rate is lower than 90%, increase the buffer cache.

- Shared Pool Memory

• Determine the size according to the SHARED POOL MEMORY item in v$sga after executing major workloads.

• If the shared pool usage is too high (insufficient free area), increase the shared pool memory.

• At least 1 MB of the shared pool memory is required for each session.

Calculating the Size

The size of each area in the shared memory can be checked with v$sga.

The size of the shared memory can be set and queried with the following initialization parameters.

Shared Memory

The following example queries the size with the TOTAL_SHM_SIZE parameter.

Buffer Cache

The following example queries the size with the DB_CACHE_SIZE parameter.

• Single mode : ⅔ of TOTAL_SHM_SIZE

• TAC mode : ½ of TOTAL_SHM_SIZE

Log Buffer

The following example queries the size with the LOG_BUFFER parameter. (the default value of LOG_BUFFER is 10 MB.)

Shared Pool Memory

The size can be calculated by subtracting the fixed memory size from the total shared memory size as follows:

• Single mode The total shared pool size must be greater than _MIN_SHARED_POOL_SIZE.

• TAC mode Sufficient space for Cluster Cache Control (CCC) and Cluster Wait-lock Service (CWS) is required. About 25% of a total buffer cache size is used by shared pools.

  The shared pool space excluding space for CCC and CWS must be greater than

  _MIN_SHARED_POOL_SIZE.

The free shared pool size for PP and DD caches must be greater than CCC and CWS spaces.

Overview

tbdv is a utility that checks integrity of data files in a Tibero database. It can perform basic integrity checks on data files while the database is offline.

tbdv checks the following for each data block.

• Is a block marked with the correct DBA?

• Does the block checksum match?

• Do the used and available spaces of a block add up to the total block size?

• Do the row pieces of a block not overlap with other row pieces ?

If an integrity check discovers an error, it is assumed to be a media failure and a media recovery must be performed on the database.

Quick Start

tbdv is automatically installed and uninstalled along with Tibero.

The following shows how to execute tbdv at a command prompt.

To set the block size, use the -s option (default value: 8,192 bytes).

To check only the specified length ofa file from the beginning, use the CHECK_LENGTH option. If this option is not specified, the entire file is checked. To use a raw device, explicitly set the device size. If not set, an error occurs.

The following executes tbdv.

Executing tbdv

Usage Example

This section describes how tbdv checks integrity of data files.

If a block is marked with incorrect DBA, tbdv displays the following.

When a Block Is Marked with Incorrect DBA

If a fractured block is found in a data file, tbdv displays the following.

When a Fractured Block Is Found

If available and used spaces for data blocks does not sum up to the total block size, tbdv displays the following.

When the Available and Used Spaces in a Block Sums up Incorrectly

Overview

IIn-Memory Column Store (IMCS) is a memory storage architecture optimized for column scans, which stores and manages data copies in a columnar format.

The columnar storage format is supported in addition to the traditional row-oriented storage, to improve database performance in a mixed environment handling both OLTP and OLAP workloads.

[Figure 1] Row-based storage vs Column-based storage

Features of In-Memory Column Store

In-Memory Area

IMCS resides in the In-Memory Area, a component of the shared memory. The size of the In-Memory Area is allocated at startup of the database and remains fixed until the next startup.

Unlike the buffer cache, which discards unused data when filled up, IMCS keeps data permanently in the In-Memory Area unless manipulated through a command by the user. This eliminates additional I/O costs when reading data stored IMCS. (However, if no valid data is found through an in-memory scan, I/O costs may incur because the buffer cache needs to be additionally read).

Columnar Format

IMCS stores copies of data in a columnar format optimized for scans. Data stored in a columnar format has an internally fixed size, which enables efficient filter operation (ex. <, >, =) during a scan.

Compression

IMCS eliminates duplicate data by compressing each columnar data. This improves memory efficiency and scan performance by reducing the number of data to be scanned.

Data Pruning

IMCS manages each columnar data in a storage unit called In-Memory Compression Unit (IMCU). IMCU contains information about the minimum and maximum values of each columnar data. Based on these minimum and maximum values of data in each IMCU, the database performs IMCU pruning to eliminate unnecessary scans and improve thus the scanning performance.

In-Memory Column Store Architecture

The In-Memory Area is allocated in a fixed location within the shared memory at startup of the database. The size of the In-Memory Area is set by the INMEMORY_SIZE initialization parameter.

The In-Memory Area is divided into two subpools: In-Memory Compression Unit (IMCU) for columnar data, and Snapshot Metadata Unit (SMU) for metadata of columnar data.

[Figure 2] In-Memory Column Store Architecture

In-Memory Compression Unit(IMCU)

An In-Memory Compression Unit (IMCU) is a storage unit of IMCS that contains data for one or more columns in a compressed format. The size of an IMCU is 1 MB, and IMCS stores data for a single object (ex. table, partition or subpartition) to multiple IMCUs in columnar format.

An IMCU stores columnar data for only one object, and every IMCU contains one or more Column Compression Units (CU).

• Column Compression Unit(CU) A Column Compression Unit (CU) is a storage for a single column in an IMCU. A CU encodes the column value of each row in a 2-byte value, which is called a dictionary code. A CU contains a mapping table for each dictionary code corresponding to the actual column data.

Snapshot Metadata Unit (SMU)

A Snapshot Metadata Unit (SMU) stores metadata for an associated IMCU. In IMCS, each IMCU is mapped to a separate SMU. Every SMU contains information about the object and the address of a data block populated in each associated IMCU, as well as a transaction journal, which records rows modified with DML statements.

In-Memory Process Architecture

Population, which converts data into columnar format in IMCS, is performed by background processes. At startup of the database, agent processes initiate population of objects having In-Memory priority. When initially accessing objects with no priority, agent processes populate them by using queries.

Reading columnar data for objects populated in IMCS through queries, or recording transaction journals in SMUs using DML statements are performed by worker processes.

SIMD Vector Processing

SIMD (Single Instruction, Multiple Data) vector processing enhances performance of expressions in a WHERE clause, by scanning a set of column values in a single CPU instruction. For example, 8 values (2-byte data) from a CU are loaded into the CPU, to get 8 results in a single comparison instruction.

SIMD is used for comparing In-Memory columns to bind parameters or constant values. The following comparison operators are supported: >, >=, =, <, <=, AND

Overview

This guide is intended for developers who want to develop applications by using Tibero Data Provider for .NET functions provided by Tibero.

Required Knowledge

• Database

• RDBMS

• .NET framework

System Requirements

Document Organization

The guide contains 3 chapters.

Tibero Spatial provides functions to save and use spatial data in Geographic Information Systems (GIS) and circuit diagrams.

GEOMETRY Objects

Tibero Spatial supports seven types of GEOMETRY objects that comply with the SQL-MM standard.

The following table describes each type of GEOMETRY objects. The object is saved as binary in Well Known Binary (WKB) format. Coordinates of GEOMETRY objects in the WKB format are saved as floating point numbers. Therefore, the result of calculations on the numbers may have some errors, and the result values may be different depending on the floating point calculation method.

Spatial Referencing System(SRS)

Tibero Spatial supports the following coordinate systems that calculate coordinates for depicting real space by connecting them with real space. Depending on which coordinate system GEOMETRY belongs to, the result value of Spatial functions may vary.

Cartesian Coordinate

A coordinate system in which a position in space is expressed on a two-dimensional plane or a three-dimensional space. It is useful when depicting a local space where the curvature of the earth is not revealed. In Spatial, SRID is not specified. GEOMETRY is basically operated in the Cartesian coordinate system. GEOMETRY without a specified SRID is calculated in this Cartesian coordinate system by default.

Spherical Coordinate (Geography coordinate)

A coordinate system in which a position in space is expressed on a two-dimensional spherical or ellipsoidal surface (spheroid). This system approaches the actual location through latitude and longitude. It is useful when accurately depicting global space. In general, a sphere or spheroid is used to express the actual position on the earth. The radius, major radius, and minor radius information of a sphere or spheroid used in this system depends on SRID given to GEOMETRY. You cannot individually store different spheroids for each GEOMETRY.

SRID(Spatial Reference Identifier)

Spatial provides SRID, which is the identifier type of the coordinate system. SRID has information about a specific coordinate system, including whether the coordinate system for GEOMETRY is the Cartesian coordinate system or the spherical coordinate system.

Overview

This guide is intended for database administrators (DBA) who intend to use Tibero. This guide describes the program structure and usage of tbCLI.

Required Knowledge

• Database

• RDBMS

• SQL

System Requirements

Document Organization

The guide contains 5 chapters.

Overview

This guide is intended for developers who develop TEXT applications and administrators who maintain TEXT systems using Tibero® (hereafter Tibero).

Required Knowledge

• Database

• RDBMS

• SQL

Document Organization

This guide consists of 4 chapters.

Failover

tbJDBC provides capability to recover some resources automatically when you initiate a connection in a typical application or TAC configuration, or when the connection is lost during a job processing. This capability is referred to as failover.

Configuring Failover

To use the failover capability, specify the URL of DriverManager.getConnection() in a description format and configure FAILOVER.

Set FAILOVER to one of the following values.

The following example enables failover. When an attempt to connect to svr1 fails, an automatic reattempt occurs to connect to svr2. If all attempts to connect to every server fail, an error occurs.

Failover-related Connection Properties

The following property specifies the maximum number of reattempts to reestablish a connection when the failover capability is enabled.

• failover_retry_count

The following properties prevent a client from waiting for a connection infinitely when the client cannot detect a disconnection because of an error.

• login_timeout

• read_timeout

• self_keepalive

Load balancing

tbJDBC provides also an ability to distribute users across multiple nodes in a typical application or TAC configuration, to increase the efficiency of database servers. This ability is referred to as load balancing.. To use the load balancing capability, specify the URL of DriverManager.getConnection() in a description format, and add (load_balance=on).

The following example enables load balancing to distribute users to svr1 and svr2 when initiating connection to servers.

Data stored in Tibero may contain sensitive information such as a personal identification number (a resident registration number) or a bank account number. This information can by potentially compromised by an unauthorized user, therefore a particular measure to authenticate the servers and clients is required to prevent any unauthorized access. To this end, tbJDBC provides Secure Sockets Layer (SSL).

The SSL function of tbJDBC has been implemented using the Java Secure Socket Extension (JSSE) package. Information between tbJDBC and the Tibero server can be protected with this function.

Configuring SSL

To use the SSL function, the Tibero server and tbJDBC must be set up. After the two are successfully set up, all information exchanged between the Tibero server and tbJDBC can be protected without any other additional processes.

Configuring Tibero Server

Tibero servers must be set up according to the following steps.

1. Check whether the authentication files exist.

1. In the $TB_SID.tip file, add the following initialization parameters.

1. Restart the Tibero server.

Configuring tbJDBC

tbJDBC must be set up as follows:

The following are the options that can be used with system.sh(vbs).

The following describes each option.

Overview

This guide is intended for database users who use the various utilities provided by Tibero.

Overview

This guide is intended for application developers who want to use the JDBC functions provided by Tibero® (Tibero) to develop applications.

If data is updated frequently in a system, a large volume of I/O happens in the undo tablespace. In such systems, data needs to be distributed by creating the undo tablespace with multiple data files.

The undo tablespace is automatically managed, providing the following advantages.

• Helps design and manage efficiently with rollback capability and segments

• Prevents undo data from being overwritten

Overview

This guide is intended for TAS administrators who want to manage Tibero® (hereafter Tibero) files by using Tibero® Active Storage (hereafter TAS).

User Configuration Files

TB_HOME

Issue

If the property TB_HOME is not set or is set improperly, or if the user configuration file is not applied after Tibero is installed, this message may be displayed when trying to connect to the tbSQL utility.

Solution

Check the TB_HOME property in the user configuration file, change the value if necessary, and then apply the file to the system.

LD_LIBRARY_PATH

Issue

If the property LD_LIBRARY_PATH is not set or is set improperly, or if the user configuration file is not applied after Tibero is installed, this message may be displayed when trying to connect to the tbSQL utility.

Solution

Check the LD_LIBRARY_PATH property in the user configuration file, change the value if necessary, and then apply the file to the system.

TB_SID

Issue

If TB_SID is not set, this message may be displayed when the tbboot or tbdown command is executed.

Solution

Check the TB_SID property in the user configuration file, change the value if necessary, and then apply the file to the system.

TAC Installation

The following describes how to resolve issues that can occur after Tibero is installed in a TAC environment.

Adding a Node

Accessing a tip File

Issue

If a configuration file (.tip) cannot be found when a node is added, this message may be displayed.

Solution

Check whether the Tibero instance's $TB_SID.tip exists in the corresponding path by referring to TB_HOME and TB_SID.

Accessing TAC

Issue

To add a node, an existing node's setting values are necessary. If trying to access an existing node fails, this message may be displayed.

Solution

• Check that TB_HOME and TB_SID are set properly.

• Check that the existing node can be accessed through tbsql.

• If an existing node does not work, start the node with the tbcm, tbboot commands then try to add the node again.

Transferring an scp File

Issue

If transferring Tibero installation files to a new node fails, this message may be displayed.

Solution

• Check whether the current node can access the node to be added using ping or ssh.

• If the current node cannot access the node to be added, check the settings for account synchronization, networking, and any firewalls.

TPR-Related Error When Using a TAC Raw Device

Issue

The SYSSUB tablespace, which contains TPR-related tables, was added starting from Tibero 5.0 r61295. During the system schema configuration portion of installing and patching, the syssub001.dtf file is automatically created in the directory $TB_ HOME/database/$TB_SID. However, if the property DB_CREATE_FILE_DEST is set to a specific location, the file is created at that location.

However, in an environment using a TAC raw device, the file is created on the local disk of the node processing the system schema. This results in an error that prevents other nodes from accessing the SYSSUB tablespace. The same error occurs in a shared disk environment when the property, DB_CREATE_FILE_DEST, is not set correctly.

Solution

Recreate the SYSSUB tablespace as follows:

1. Delete the existing tablespace.

1. Create a new tablespace.

1. Execute the following script.

Miscellaneous

Port Number

Issue

This error occurs when the specified port number is already in use when executing the tbboot command.

Solution Check whether the instance is already in use or modify the port number set in the $TB_SID.tip file in $TB_HOME/client/config.

dbtimezone

Recommendation

The dbtimezone is the reference timezone value used for storing the timestamp with local timezone data to database. Since this value is internally processed in the database, it is not recommended to modify it, because this requires unnecessary operations leading to performance degradation.

Creating Spatial Indexes

The following describes how to create a Spatial index.

Usage

Example

Spatial Index Constraints

Spatial indexes have the following constraints.

• A single index cannot be used for multiple columns.

• A Spatial index cannot be partitioned.

• A Spatial index cannot be created for non-GEOMETRY type columns.

• A Spatial index can be used only when the following functions are implemented in a WHERE clause of SQL statements. - ST_CONTAINS - ST_COVEREDBY - ST_COVERS - ST_CROSSES - ST_DWITHIN - ST_EQUALS - ST_INTERSECTS - ST_OVERLAPS - ST_TOUCHES - ST_WITHIN

A Spatial index of the spheroid coordinate system can be created by adding a constraint to the GEOMETRY column of the table.

Usage

Example

In some cases, it is necessary to change the coordinate system of the existing GEOMETRY column and create a Spatial index. If there are existing constraints, delete them, change the SRID of GEOMETRY, and then add appropriate constraints for the SRID to create the Spatial index.

Usage

Example

Dropping Spatial Indexes

The following describes how to drop a Spatial index.

The method is the same as for other indexes.

Usage

Overview

This guide is intended for database administrators (DBA) who choose to refer to tbPSM, the persistent stored module provided by Tibero® (Tibero), and application program developers.

Required Knowledge

• Database

• RDBMS

• SQL

• tbPSM

System Requirements

Document Organization

The guide contains 8 chapters.

A row set is an object that includes a set of row data. It can be accessed using the javax.sql.RowSet object.

There are three kinds of row sets.

• Cached Row Set(tbJDBC currently provides this row set only.)

• JDBC Row Set

• Web Row Set

Row Set Listener

Multiple listeners can be registered to a row set. To register a listener, the addRowSetListener() method is used, and to delete a listener, the removeRowSetListener() method is used. The listener must be implemented using the javax.sql.RowSetListener interface.

The RowSetListener interface provides the following events.

The events of the RowSetListener interface are used as follows:

1. Create a listener class.

1. Register the listener to a list of RowSet objects.

Cached Row Set

A Cached Row Set is a row set that stores all rows in a cache, and is not connected to the database. In tbJDBC, a Cached Row Set is provided as the TbCachedRowSet class.

Creating a RowSet Object

A RowSet object is initialized using the execute() method, and can then be used in the same way as a java.sql.ResultSet object.

This section describes two ways to create a RowSet object.

Creating a RowSet Object Using a Query

The following example illustrates how to create a RowSet object using a query.

1. Create a TbCachedRowSet.

1. Specify the URL, user name, password, and query, and then create a RowSet object by calling the execute() method.

Creating a RowSet Object using a Result Set

The following example shows how to create a RowSet object using an existing result set.

1. Create a TbCachedRowSet object.

1. Create a RowSet object by calling the populate() method with a result set object (rset).

Searching Rows

It is possible to search rows by moving forward or backward with a RowSet object.

The following is an example.

It is also possible to insert, delete, or modify rows. The acceptChanges() method must be called to commit any changes.

The following is an example.

Restrictions

The restrictions on row sets are the same as those for updatable result sets.

Installation in manual mode

1. Prepare the installation file. When you create a folder to install the Tibero client and unzip it, folders are created.

2. Configure the invironment variables.

(1) In Windows, select [Edit system environment variables] -> [Advanced] -> [Environment variables] and configure [System variables].

[Figure 2] Configuring system variables

(2) In the [Environment variable], select [System variables] -> [New] and configure TB_HOME and TB_SID.

[Figure 3] TB_HOME and TB_SID configuration

(3) Unzip the compressed binary executable file(tar.gz) in the directory ‘C:\Tibero'. Then, copy the license file(license.xml) into the subdirectory named “license’ under %TB_HOME%.

(4) After executing tbinstall.vbs, and check the registry registration.

[Figure 4] installation complete message

In the registry (regedit), check whether TB_HOME and TB_SID are registered in the HKEY_LOCAL_MACHINE\SOFTWARE\TmaxTibero\Tibero\tibero path.

[Figure 5] TB_HOME, TB_SID registration check

(5) Execute gen_tip.bat.

(6) Delete any unnecessary folders except ‘bin’ and ‘client’ folders.

(7) Configure the network file(tbdsn).

(8) Access to Tibero Server with Tibero Client.

Uninstallation

1. Execute tbuninstall.vbs and remove it from the registry.

[Figure 6] Uninstallation complete message

1. Delete physical files. Uninstall the Tibero client by deleting the directory in the path set to %TB_HOME%.

In-Memory Initialization Parameters

INMEMORY_SIZE

JDBC

JDBC (Java Database Connectivity) is an API (Application Programming Interface) that allows Java programs to access a database to execute SQL statements.

JDBC provides the following advantages.

• Use SQL statements in any relational database.

Linux

This section describes how to configure HugePage in Linux. Root permission is required.

Enabling HugePage

The following describes how to enable HugePage.

1. Check the size of HugePage supported in the current OS.

1. Check the user group ID that runs Tibero.

1. Apply the groups and number that will allocate HugePage in "/etc/sysctl.conf"

The following is an example of applying the kernel parameter when TOTAL_SHM_SIZE is set to 1024 MB and the size of HugePage supported by the current OS is 2 MB (2048 KB).

1. Apply the maximum locked memory value in "/etc/security/limits.conf".

The following is an example of configuring the memlock value.

1. Restart the operating system.

The modified HugePage value has been applied.

1. Configure the Tibero initialization parameters in the configuration file (.tip).