Netezza books pdf free download

Read, enjoy, and share! No fee or registration! Everything from Project Gutenberg is gratis, libre, and completely without cost to readers. If you find Project Gutenberg useful, please consider a small donation to help Project Gutenberg digitize more books, maintain its online presence, and improve Project Gutenberg programs and offerings. Other ways to help include digitizing, proofreading and formatting, or reporting errors.

No special apps needed! What is Scribd? Babu Netezza. Uploaded by Manoj Kumar. Did you find this document useful? Is this content inappropriate? Report this Document. Flag for inappropriate content. Download now. It is a user friendly tool for development work and adhoc queries and also provides GUI options to perform database management tasks.

Netezza Objects Netezza appliance comes out of the box loaded with some objects which are referred to as system objects and users can create objects to develop applications which are referred as user objects. In this section we will look into the details about the basic Netezza objects which every user of the appliance need to be aware of. They are used to perform all the administration tasks and hence should be used by restricted number of users. User id Description root The super user for the host system on the appliance and has all the access as a super user in any Linux system.

Groups By default Netezza comes with a database group called public. All database users created in the system are automatically added as members of this group and cannot be removed from this group. Permissions can be set to the public group so that all the users added to the system get those permissions by default. Databases Netezza comes with two databases System and a model database both owned by Admin user. The system database consists of objects like tables, views, synonyms, functions and procedures.

The system database is primarily used to catalog all user database and user object details which will be used by the host when parsing, validating and creation of execution code for queries from the users. User Objects: Database Users with the required permission or an admin user can create databases using the create database sql statement.

The following is a sample SQL to create a database called testdb and it can be executed in an nzsql session or other query execution tool. The following is a sample table creation statement which can be executed in an nzsql session or other query execution tool. Also there are no storage related details like tablespace on which the table needs to be created or any bufferpool details which are handled by the Netezza appliance.

The following is the list of all the data types supported by the Netezza appliance which can be used in the column definitions of tables. The default value of n is 1. The maximum character string size is 64, If n is equal to 16 or less then n bytes. If n is greater than 16, disk usage is the same as varchar n. No blank padding, stored as entered. The maximum length of 16, characters. Ranging from January 1, It is up to the application to make sure that these constraints are satisfied by the data being loaded into the tables.

Even though the constraints are not enforced by Netezza defining them will provide additional hints to the query optimizer to generate efficient snippet execution code which in turn helps performance. Users can also create temporary table in Netezza which will get dropped at the end of the transaction or session in which the temp table is created.

This can be accomplished in Netezza using the create table as command and are referred as CTAS tables in short. The following is an example Renaming the table, changing the owner of the table, adding or dropping a new column, renaming a column, adding or dropping a constraint are some of the modifications which can be made through the alter statement.

The following are sample alter statements which can be executed through nzsql session or a query execution tool. The stored procedure needs to be dropped first before adding or dropping a column and then the stored procedure needs to be recreated. View The database owner or user with create view privilege can create views in a database. The SQL gets executed pulling the data from the base table whenever a user accesses the view creating a virtual table.

The following is a sample view creation statement which can be executed in an nzsql session or other query execution tool. Materialized views can be queried directly or can be used to improve performance against the base table. In the latter case, the materialized view acts like an index since the system stores an additional column in the view with the details about from where in the base table that data originated. A database owner or user with create materialized view privilege can create materialized view in a database.

The following is a sample materialized view creation statement which can be executed in an nzsql session or query execution tools. But the new data getting inserted will not be in the sorted order and hence there will be some data in the materialized data which are not in the sorted order.

In order to get the materialized view in sorted order, the views need to refreshed periodically or threshold of unsorted data as a percentage of total records can be set so that the system performs the refresh when the percentage of unsorted records in the table exceeds the threshold.

Synonym A synonym is an alternate way of referencing tables and views. It allows users to create easy to type names for long table or view names.

An admin user or any user with create synonym privilege can create synonyms in a database and the following is a sample statement to create synonym through an nzsql session or other query execution tool.

But if the table or view referred by a synonym is not existent during runtime an error message will be returned. Synonyms cannot be created for temporary tables, remote databases or other synonyms. Sequence The following is a sample sequence creation statement which can be used to populate the id column in the employee table. That would mean the sequences generated by the various SPUs will create gaps in the sequence numbers at any point in time since the ranges will not be over lapping.

Some of the modifications are changing the owner, renaming the sequence, restarting the sequence with a new start value, change the increment value or max value and whether the sequence should or should not reuse the old values once it has reached its max value. Functions We will look into the details about user defined functions when we discuss about application development. Netezza Security This section deals with security in the context of user access to the appliance.

In Netezza there are two levels of access controls, one at the host OS level and second at the Netezza database level. By setting the required access restrictions at these two levels, the appliance can be secured effectively. OS Level Security Netezza host uses industry standard Linux operating system customized for performance and functionality required for the appliance. As in any Linux installations, user access restrictions need to be put in place using user ids, user groups and passwords.

Since the host access is required to perform very restricted tasks primarily administration tasks, the number of user ids created to access the appliance should be fairly small. Restrictions on what users can perform can be set by creating Linux user groups with different access restrictions and attaching the relevant users to the groups.

Setting password selection rules like mix of alphabets, numbers, special characters, minimum password length etc. Database Level Security Access to databases is controlled using user ids and passwords which are separate from the OS level user id and password.

Access to databases, objects with in a database and the type of activities which can be performed on them are all controlled by the privileges granted to the user id to perform the task.

Netezza also supports user groups as with the Linux operating system where privileges can be assigned to groups and similar users can be attached to the group so that it is easier to manage access to databases.

When a user id is attached to more than one group the user id gets combination of all the privileges assigned to the groups to which the user id is attached to. Netezza Storage As discussed earlier, each disk in the appliance is partitioned into primary, mirror and temp or swap partitions. The logical representation of the data saved in the primary partition of each disk is called the data slice.

When users create database tables and loads data into it, they get distributed across the available data slices. Logical representation of data slices is called the data partition. For TwinFin systems each S-Blade or SPU is connected to 8 data partitions and some only to 6 disk partitions since some disks are reserved for failovers. The following diagram illustrates this concept The SPU is connected to 8 data partitions numbered 0 to 7. Each data partition is connected to one data slice stored on different disks.

The disk also stores the mirror of the data slice 18 stored on disk The following diagram illustrates what happens when the disk fails. Immediately after the disk stops responding, the disk will be used by the system to satify queries for which data is required from data slice 23 and Disk will serve the requests using the data in both its primary and mirror partition. This will also create a bottleneck which inturn impacts query performances.

In the meantime, the contents in disk are regenerated on one of the spare Once the regen is complete the SPU data partition 7 is updated to point to the data slice 24 on disk The regen process removes the bottleneck of disk to perform optimally.

Pairs of disks which contains the mirror copy of each others data slice will be assigned to other SPUs which will result in additional two data partitioned to be managed by the target SPU. If for e. Data Organization When users create tables in databases and store data into it, data gets stored in disk extents which is the minimum storage allocated on disks for data storage.

Netezza distributes the data in data extents across all the available data slices based on the distribution key specified during the table creation. A user can specify upto four columns for data distribution or can specify the data to be distributed randomly or none at all during the table creation process. If an user provides no distribution specification, Netezza uses one of the columns to distribute the data and the selection of which cannot be influenced. When the user specifies particular column for distribution then Netezza uses the column data to distribute the records being inserted across the dataslices.

Netezza uses hashing to determine the dataslice into which the record needs to be stored. When the user selects random as the option for data distribution, then the appliance uses round robin algorithm to distribute the data uniformly across all the available dataslices.

The following are some sample table create statements using the distribute clause. By distributing data across the data slices, all the SPUs in the system can be utilized to process any query and in turn improves performance. Also the performance of any query depends on the slowest SPUs handling the query.

So if the data is not uniformly distributed then some Selecting columns with high cardinality for the distribution is a good practice to follow. Even if a column with high cardinality like a date column is chosen to distribute data, there is a possibility of creating processing skew.

Product Capabilities. All User Ratings. I like the Netezza product and what it offers. My only concern is that the End of Life on the equipment are too short. Hence, I have to spend few million dollars almost every three years which isn't ideal.

But as for the product itself, it does the job and then some. New Decimal Delimiter Option.