Properties and effects of the new attribute clustering feature
Posted: Mon Jan 27, 2025 4:50 am
Attribute clustering means that I tell the database via metadata definition that the data in a heap table should be organized according to one or more criteria. Data with the same characteristics of these criteria are therefore physically stored contiguously in the table, which means that for read access only as many blocks need to be accessed as allocate these contiguously stored data. When using Exadata storage indexes as part of the so-called "smart scans " ( full table scan is outsourced to Exadata's storage cells ), in-memory column store- based full table scans or zone maps (unfortunately only available in Exadata environments for licensing reasons), this even applies to full table scans , so these can also be significantly accelerated/optimized by attribute clustering, since only the relevant areas of the table are processed and the rest is "ignored"/skipped - otherwise especially with index-based access patterns.
So what would the use of algeria telegram screening attribute clustering look like in this specific example? The CREATE TABLE command to create a corresponding heap table with attribute clustering could look like this:
Instead of the ORGANIZATION INDEX option, the CLUSTERING BY option is now used, which tells the database that the data in the heap table should be physically stored contiguously according to the specified criteria. This can also be defined subsequently for existing tables using ALTER TABLE , or it can be removed later and replaced by another clustering definition.
LINEAR ORDER is the standard case and means that if multiple criteria are specified - here TICKER_CODE and TRADE_DATE - the data is first stored primarily according to TICKER_CODE and, if there are multiple rows with the same TICKER_CODE , then data that is related according to TRADE_DATE is stored. This means that this type of clustering is only beneficial for queries that primarily query for the TICKER_CODE and possibly also for the TRADE_DATE , but not for queries that only query for the TRADE_DATE because the primary criterion is the TICKER_CODE . The data is not stored together according to TRADE_DATE but only together according to TRADE_DATE if the TICKER_CODE is the same within this set.
So what would the use of algeria telegram screening attribute clustering look like in this specific example? The CREATE TABLE command to create a corresponding heap table with attribute clustering could look like this:
Instead of the ORGANIZATION INDEX option, the CLUSTERING BY option is now used, which tells the database that the data in the heap table should be physically stored contiguously according to the specified criteria. This can also be defined subsequently for existing tables using ALTER TABLE , or it can be removed later and replaced by another clustering definition.
LINEAR ORDER is the standard case and means that if multiple criteria are specified - here TICKER_CODE and TRADE_DATE - the data is first stored primarily according to TICKER_CODE and, if there are multiple rows with the same TICKER_CODE , then data that is related according to TRADE_DATE is stored. This means that this type of clustering is only beneficial for queries that primarily query for the TICKER_CODE and possibly also for the TRADE_DATE , but not for queries that only query for the TRADE_DATE because the primary criterion is the TICKER_CODE . The data is not stored together according to TRADE_DATE but only together according to TRADE_DATE if the TICKER_CODE is the same within this set.