Hypercharge Oracle data loading performance: speed tips
Oracle Tips by Burleson Consulting
February 17, 2015
Is there any limit to the speed of Oracle? With Oracle announcing a new record one million transactions per minute, many believe that there is nothing that Oracle cannot do.
The fastest Oracle table insert rate I’ve ever seen was 400,000 rows per second, about 24 millions rows per minute, using super-fast RAM disk (SSD), but Greg Rahn of Oracle notes SQL insert rates of upwards of 6 million rows per second using the Exadata firmware:
One of the faster bulk (parallel nologging direct path from external table using direct path compression) load rates I’ve seen is just over 7.7 billion rows in under 20 minutes which equates to around 385,000,000 per minute or about 6,416,666 per second.
All the CPUs are running at around 99% user CPU during that load. That was loading to spinning rust (Exadata Storage). It would be even faster had compression not been used. That was on a HP Oracle DB Machine (64 Intel Harpertown CPU cores).
However, what if we have a requirement for a system that must accept high-volume data loads into a single table:
500,000 rows per second
50 megabytes per second
Is this possible? Using the right tricks you an make Oracle load data at unbelievable speed. However, special knowledge and tricks are required.
Oracle provides us with many choices for data loading, some way faster than others:
SQL insert and merge statements
PL/SQL bulk loads for the forall PL/SQL operator
Oracle Data Pump
Batch Data Loading
If you are loading your data from flat files there are many products and Oracle tools to improve your load speed:
Oracle Data Pump (available January 2004) – With Data Pump Import, a single stream of data load is about 15-45 times faster than original Import. This is because original Import uses only conventional mode inserts, whereas Data Pump Import uses the direct path method of loading. Oracle SQL*Loader – Oracle SQL*Loader has dozens of options including direct-path loads, unrecoverable, etc and get super-fast loads. Here are tips for getting high-speed loads with SQL*Loader. BMC Fast Import for Oracle – Claims to be 2 to 5x faster than Oracle import utility.
CoSORT FAst extraCT (FACT) for Oracle – Claims to get Bulk loads up to 90% faster when CoSORT pre-sorts the load file on the table’s index key. This also improves clustering_factor and improves run-time SQL access speeds by reducing logical I/O.
Tips for super fast data loading
Don’t use standard SQL insets as they are far slower than other approaches. If you must use SQL inserts, make sure to use the APPEND hint to bypass the freelists and raise the high-water mark for the table. You are way better off using PL/SQL with the bulk insert features (up to 100x faster).
Don’t use standard SQL insets – They are far slower than other approaches. If you must use SQL inserts, make sure to use the APPEND hint to bypass the freelists and raise the high-water mark for the table. Note: INSERT APPEND supports only the subquery syntax of the INSERT statement, not the VALUES clause. You are way better off using PL/SQL with the bulk insert features (up to 100x faster). Partition – Load the data in a separate partition, using transportable tablespaces. Use SSD RAM Disk – Especially for the insert partition, undo and redo. You can move the partition to standard disk later. Use parallel DML – Parallelize the data loads according to the number of processors and disk layout. Try to saturate your processors with parallel processes. Disable constraints and indexes – Disable during load and re-enable in parallel following the load. Use multiple freelists or freelist groups for target tables – Avoid using bitmap freelists ASS management (automatic segment space management) for super high-volume loads. Pre-sort the data in index key order – This will make subsequent SQL run far faster for index range scans. Size your log_buffer properly – If you have waits associated to log_buffer size ?db log sync wait. try increasing to to 10m. Use RAM Disk – Place undo tablespace and online redo logs on Solid-state disk (RAM SAN), Use SAME RAID – Avoid RAID5 and use Oracle Stripe and Mirror Everywhere approach (RAID 1+0, RAID10). Use a small db_cache_size – If loading with DML a small data cache will minimize DBWR work during async buffer cleanouts. In Oracle you can use the alter system set db_cache_size command to temporarily reduce the data buffer cache size. Watch your commit frequency – At each commit, Oracle releases locks and undo segments. Benchmarks suggest that you should commit as infrequently as possible and use vary large undo segments to avoid a ORA-1555 (snapshot too old) error.
Use a large blocksize – Data loads onto 32k blocksizes will run far faster because Oracle will be able to insert more rows into an empty block before a write.
For more information and details, I’m available to assist with your high-speed loading needs.
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