Teradata Parallel Data Pump

Chapter 1: Overview
Teradata TPump Utility
Economy of Scale and Performance
MultiLoad performance improves as change volume increases because, in phase two of
MultiLoad, changes are applied to target tables in a single pass. All changes for any physical
data block are effected using one read and one write of the block. Furthermore, the temporary
table and the sorting process used by MultiLoad are additional overheads that must be
“amortized” through the volume of changes.
Teradata TPump, on the other hand, performs better for relatively low change volume because
there is no temporary table overhead. Teradata TPump becomes expensive for large volumes
of data because multiple updates to a physical data block will most likely result in multiple
reads and writes of the block.
Loading No Primary Index (NoPI) Tables
A NoPI table has no primary index. These tables can be used as staging tables where data is
always appended to the table, making population of the table generally faster than that of a
traditional table containing a primary index.
NoPI tables could increase performance for Teradata TPump Array INSERT.
Multiple Statement Requests
The most important technique used by Teradata TPump to improve performance over
MultiLoad is the multiple statement request. Placing more statements in a single request is
beneficial for two reasons. First, it reduces network overhead because large messages are more
efficient than small ones. Secondly, (in ROBUST mode) it reduces Teradata TPump recovery
overhead, which amounts to one extra database row written for each request. Teradata TPump
automatically packs multiple statements into a request based upon the PACK specification in
the BEGIN LOAD command.
Macro Creation
Teradata TPump uses macros to efficiently modify tables rather than actual DML commands.
The technique of changing statements into equivalent macros before beginning the job greatly
improves performance.
Specifically, the benefits of using macros are:
• The size of network (and channel) messages sent to the database by Teradata TPump are
reduced.
• Teradata Database parsing engine overhead is reduced because the execution plans (or
steps) for macros are cached and re-used. This eliminates normal parser handling, where
each request sent by Teradata TPump is planned and optimized.
Because the space required by macros is negligible, the only issue regarding macros is where
they are placed in the database. Macros are put into the database that contains the restart log
table or the database specified using the MACRODB keyword in the BEGIN LOAD command.
Locking and Transactional Logic
In contrast to MultiLoad, Teradata TPump uses conventional row hash locking, which allows
for some amount of concurrent read and write access to its target tables. At any point,
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