Teradata 14 is fully loaded with fantabulous features
and enhancements, particularly I like the way they have compete directly with
his peer by bringing the features like DENSE_RANK function, NUMBER
data type etc. and other features like AUTOMATED STATISTICS
MANAGEMENT,ROW-LEVEL SECUIRITY,EQUITY JOIN FOR SKEW TABLES and much more.
Handpicked the features of Teradata 13/13.10 and
Teradata 14/14.10 on developer perspective from release summaries. Hope this serves
us a quick reference.
Teradata 13
|
Teradata 14
|
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1. Collect Statistics Optimization
a)
Improved
Sampled Statistics
i) improves sampled statistics for the number of unique values for partitioning columns
b) Restrictions
Removed on Collecting
Statistics i) Multicolumn statistics on join and hash indexes ii) System-derived PARTITION statistics on partitioned join indexes iii) Single-column, multicolumn and PARTITION statistics on volatile tables iv) Statistics on unhashed tables v) Sampled statistics on the partitioning columns of PPI |
1. Collect Statistics Enhancements
a)
Adding the
SUMMARY option
to collect table-level statistics
b)
Adding a
number of internal
enhancements to the Optimizer
with respect to histogram structure
and use, including:
c)
Maintaining
statistics history.
d)
Enhancing
extrapolation methods
for stale statistics.
e)
Enhancing
sampling options.
f)
Storing
statistics data in their
native Teradata data types
without losing precision.
|
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2. Count(*) Optimization
a)
The count
function now reads
the cylinder index rather than performing a full table scan |
2. Automated
Statistics
Management
a)
Teradata
Database can manage
statistics collection for you, simplifying database administration by ensuring that the needed statistics are collected at the right time. |
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3. Dynamic partition elimination
(DPE)
a)
Enhanced
Performance of
Unspooled PPI Merge Joins |
3. Active Fallback, Phase II
a)
Phase II of
this feature repairs
the primary copy of
a data block
from fallback when an
unrecoverableb it error occurs.
Phase I allowed the data block to be
read from the fallback copy. |
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4. Group By and Distinct
Performance Equivalence
a) While
using DISTINCT, the
query optimization process rewrite it to GROUP BY at the background. So both are same now |
4.
Expansion by Business
Days
a)
Adds support
for the following
new business anchors:
WEEK_BEGIN, WEEK_END, QUARTER_BEGIN,
QUARTER_END,
YEAR_BEGIN and YEAR_END. |
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5. Handling Redundant DISTINCT Detection and Removal
a)
Internal
enhancement for Distinct
|
5. Encryption Enhancements
a)
The Blowfish
encryption
algorithm.
|
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6. Implement Smart Local
Aggregation Decisions
a) This feature
improves the performance
of many aggregate functions, such as SUM, COUNT, MIN, and MAX. |
7.
Hash Join
Enhancements
a)
Enhanced
performance of
outer
joins, inclusion and
exclusion
semi joins, joins
with partition
elimination,
and
joins with cross terms.
|
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7. Increased Join/Subquery Limit
a)
Enables More
Complex Queries
With Larger Numbers of Joins i.e. from 64 to 128. |
7. Increased Maximum Number
of Vprocs
a)
The maximum
number of
virtual processors
(vprocs)
supported per Teradata Database
system has been increased from
16,384 to 30,720.
|
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8. Inner and Outer Join Elimination Enhancements
a)
Enables
several new inner and
outer join elimination performance enhancements |
8. Increased
Partition Limits
a)
This feature
increases
limits
related to partitioned
primary indexes (PPIs) and
their
partitioning expressions.
The
new limits for partitioning
expressions
also apply to
column-partitioned
NoPI tables
and column-partitioned NoPI join indexes. |
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9. JI/AJI Enhancements
a)
Produce better
join plans by
using join indexes with Partial Group By optimizations |
9. Indexes on UDT Columns
a)
You can now
create primary
and secondary indexes on most
types of
user-defined type
(UDT) columns.
|
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10. Non-Key Access
Paths
Enhancements
a)
Better use of
access paths to
base tables and join indexes improves query performance |
10.
FastLoad
Support for
Temporal Tables
a)
FastLoad can
now inserts
into
temporal tables.
|
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11. Top N Enhancements
a)
This feature
extends the functionality
of the TOP n operator and incorporates several new processing optimizations for both TOP n and “any n” requests. |
11. Multiple WITH/WITH
RECURSIVE Clauses
a)
The number of
WITH or WITH
RECURSIVE request modifiers
that can be specified with a DML
request increases from one
to any number.
|
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12. Implicit DateTime
a)
Default
DateTime values for the CREATE/ALTER TABLE statement
|
12.
NUMBER Data
Type
a)
Increased
compatibility with
other
databases, which include
a similar NUMBER data type.
|
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13. New SHOW Access Right
a)
The SHOW
access right allows a
grantee to access a table definition without accessing any of its data. |
13. Row-Level Security
a)
Teradata
row-level security
(RLC) allows you to restrict data
access by row.
Hierarchical category:
Security Classification
i)
Labels: Top
Secret = 4,
Secret = 3,
Classified = 2,
Unclassified =
1
Non-Hierarchical category: Country
ii) Labels: USA = 4, UK = 3,
Germany = 2,
France = 1
|
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14.Simplified Query Capture
Database DBQL XML Query Plan Logging
a) Capturing Query
Capture
Database (QCD)-like information is now less complex, enabling better performance of logging query and workload information. |
14.
Secure
Password Storage
and Retrieva
a) Passwords and other logon string data in coded file locations that the Teradata Wallet application
manages tdpid/username,$tdwallet
(password_alias)
or
tdpid/username,$tdwallet
|
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15. No Primary Index
Tables
a)
The syntax for
the CREATE
TABLE statement has been changed to permit user data tables to be created without a primary index. Such tables are referred to as NoPI (No Primary Index) tables. i) Enhanced performance for FastLoad bulk data loads into staging tables. ii) Enhanced performance for TPump Array INSERT minibatch loads into staging tables |
15. SQL ARRAY/VARRAY
Data Type
a) ARRAY, a user-defined
multidimensional data type
with up to 5 dimensions and a user-defined maximum number of elements, all of the same specific data type.
b)VARRAY, an Oracle-
compatible form of the ARRAY data type. Unlike the
Oracle VARRAY data type,
the Teradata VARRAY type can be defined in multiple dimensions. |
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16. Period Data Types
a)
a Period data
type value, indicates
when a particular event starts and ends. |
16.
Temperature-Based
Block-
Level Compression
a)Teradata Database now provides
temperature-based block-level
compression (TBBLC), which
automatically compresses cold
(infrequently
accessed) data
and automatically decompresses
data when it becomes warm
(more frequently accessed).
|
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17. Transfer Statistics
a)
CREATE TABLE
AS statement
that uses the WITH DATA AND STATISTICS option. |
17. Teradata Columnar
a) Permits efficient access to
selected data, which reduces
query I/O. Adds flexibility in
defining a partitioned table or join index.Such flexibility provides opportunities to improve workload performance.
Enables the optimizer to exclude
unneeded column partitions,
significantly enhancing
query
performance.
|
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18. New Teradata Reserved Words
a. CONNECTAR
CTCONTROL CURRENT_ROLEAR
CURRENT_USERAR
b.
EXPAND
EXPANDING
c. GETAR
d.
RESIGNALAR
e.
SIGNALAR
f. UNTIL_CHANGED
g. VARIANT_TYPE
h. XMLPLAN
|
18.New Teradata
Reserved
Words
a.
NUMBER
b.
TD_ANYTYPE
|
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19. New Teradata
Nonreserved
Words
a. APPLNAME
b. CLASS_ORIGINAN
COMMAND_FUNCTIONAN COMMAND_FUNCTION_
CODEAN
c. CONDITIONAR
CONDITION_IDENTIFIERAN CONDITION_NUMBERAN
CREATOR
d.
DIAGNOSTICSAN
DOWN
e.
EXCEPTION
f.
GLOP
g.
LDIFF+
h.
MEETS+
MEMBERAR MESSAGE_LENGTHAN MESSAGE_TEXTAN MOREAN
i. NODDLTEXT
NUMBERAN
j. OLD_NEW_TABLE
OWNER
k. P_INTERSECT+
P_NORMALIZE+ PERIOD PRECEDES+ PRIORAN
l. RDIFF+ RESET
RETURNED_SQLSTATEAN ROW_COUNTAN RULES
RULESET
m. SUBCLASS_ORIGINAN
SUCCEEDS+
n. THROUGH
TRANSACTION_
ACTIVEAN
o.
XML
|
19. New Teradata Nonreserved
Words
a.
ANCHOR_HOUR
b.
ANCHOR_MILLISECOND
c.
ANCHOR_MINUTE
d.
ANCHOR_SECOND
e.
ARRAY
f.
AUTO
g.
AUTOTEMP
h.
BLOCKCOMPRESSION
i.
CALENDAR
j.
EXPORTWIDTH
k.
IPARTITION
l.
MANUAL
m.
MAXINTERVALS
n.
MAXVALUELENGTH
o.
NEVER
p.
ORDINALITY
q.
PARTITION#L16
r.
QUARTER_BEGIN
s.
QUARTER_END
t.
RANGE#L16
u.
ROWIDGEN
v.
ROWIDGEN2
w.
STATSUSAGE
x.
VARRAY
y.
WEEK_BEGIN
z.
WEEK_END
aa.
YEAR_BEGIN
bb.
YEAR_END
|
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20.
Obsolete
Teradata Tools and
Utilities Products
|
20.
Equality Joins
on Skewed
Tables
Teradata Database uses a new
hybrid join method for joins
with
equality join conditions where
one
or both sources are skewed.
The hybrid join method is called
Partial Redistribution and
Partial
Duplication (PRPD).
Teradata Database splits the
sources of the join into
separate
spools, performs several regular
joins between those separate spools
and combines the join results.
The
number of split joins is either
2
(if only one source is skewed)
or
3 (if both sources are skewed on
different values).
PRPD can be used even if the
join columns on both tables have
more than one skewed value.
The Optimizer chooses the PRPD
method only if it is less costly
than other join methods.
|
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21.
|
21. Algorithmic and Multi-Value Compression Enhancements
Multi-Value Compression (MVC)
now compresses
table columns
defined with the following data types:
a.
TIME and TIME
WITH
TIME ZONE
b.
TIMESTAMP and
TIMESTAMP
WITH TIME ZONE
Algorithmic Compression
(ALC)
now allows you to define
your own algorithms to compress and decompress columns with the following data types:
a.
TIME and TIME
WITH
TIME ZONE
b.
TIMESTAMP and
TIMESTAMP
WITH TIME ZONE
c.
BLOB/CLOB
d.
Distinct
LOB-type UDTs,
with some restrictions
|
||||||||||||
22.
|
22.
Block Level
Compression Enhancements
a)
Finer control
over the types of
tables
that are compressed.
b)
Single-command
compression of
all
qualifying tables in a database.
Improved performance from
compressing only the fallback data subtables. |
||||||||||||
23.
|
23. Derived Periods
You can now
define a derived
period column using two DateTime columns. |
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24.
|
24.
1 MB Data
Blocks
/1 MB Spool Rows
Teradata Database creates and
stores data blocks up to 1 MB
for most systems. The prior maximum data block size was 128 KB.
The maximum size of an internal
spool row is 1 MB. The prior
maximum size was 64 KB. |
||||||||||||
25.
|
25. Importing from an
Oracle Database
Provides
dynamic access to
Oracle data Allows customers to continue linking to related Oracle databases for data after migrating their data warehouse
to Teradata
|
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26.
|
26.
New Ordered
Analytical and Aggregate Functions
CUME_DIST calculates the
cumulative distribution of a value in a group of values.
DENSE_RANK returns the
rank of a row in an ordered group of rows according to the value of one or more columns, assigning the next rank value
to the next unique value in the
face of ties. Rank values are not skipped in the event of ties.
FIRST_VALUE returns the first
row from a partition.
LAST_VALUE returns the last
value from a partition. Teradata Database 14.10 supports the following new aggregate functions:
PERCENTILE_CONT takes
a percentile value and a sort specification and returns an interpolated value that would fall into that percentile value
(an inverse distribution function).
PERCENTILE_DISC takes a
percentile value and a sort specification and returns an element from the set
(an inverse distribution
function).
MEDIAN is a specific case of
PERCENTILE_CONT where
the percentile value is 0.5. |
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27.
|
27. Sort Ordering of NULL
Values
you can specify
whether NULL
values sort first or last in:
You have more
control and
flexibility with respect to sort ordering of NULL values. |
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28.
|
28.
Update-Delete-Insert
Counts
Tracks the number of insert,
delete, and update operations performed on tables in Teradata Database to better enable the Optimizer to estimate cardinalities. |
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29.
|
29. Teradata Intelligent Memory
The permanent
table data used
most often now
remains in-memory
for faster
access. The data stays in
VERYHOT cache
until other data
is used more often and replaces
it in the
cache.
Teradata
Virtual Storage (TVS)
automatically
determines the hottest
data.
|
Blog is open for your comments and suggestions!!
Great and Valuable Information about teradata 14.....Biswadip
ReplyDeleteYour point 15)b. is not correct. Oracle supports multi-dimensional VArray from 9i (Year 2005) onward. Current version is 12c. You should rectify this.
ReplyDeletePlease find the following code -
SQL> CREATE OR REPLACE TYPE name_type_size IS VARRAY ( 3 ) OF VARCHAR2 ( 50 );
2 /
Type created .
SQL> CREATE OR REPLACE TYPE name_type_size_array IS VARRAY ( 200 ) OF name_type_size ;
2 /
Type created .
SQL> DECLARE
2 i_name_type_size_array name_type_size_array := name_type_size_array ();
3 BEGIN
4 FOR count1 IN 1 .. 200 LOOP
5
6 i_name_type_size_array . EXTEND ;
7 i_name_type_size_array ( count1 ) := name_type_size ();
8
9 FOR count2 IN 1 .. 3 LOOP
10
11 i_name_type_size_array ( count1 ). EXTEND ;
12 i_name_type_size_array ( count1 ) ( count2 ) := count2 ;
13
14 END LOOP;
15
16 END LOOP;
17 END;
18 /
PL /SQL procedure successfully completed .
SQL>
please share the differences between 14 and 15 also..
ReplyDeleteThanks for info.
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