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Exadata

Exadata Zone Maps

Just a quick post on a new Exadata feature called Zone Maps. They’re similar to storage indexes on Exadata, but with more control (you can define the columns and how the data is refreshed for example). People have complained for years that storage indexes provided no control mechanisms, but now we have a way to exert our God given rights as DBA’s to control yet another aspect of the database. Here’s a link to the 12.1.0.2 documentation which resides in the Data Warehousing Guide: Zone Map Documentation

Zone Maps are restricted to Exadata storage by the way (well probably they work on ZFS and Pillar too). Have a look at the Oracle error messages file:

Why Write-Through is still the default Flash Cache Mode on #Exadata X-4

The Flash Cache Mode still defaults to Write-Through on Exadata X-4 because most customers are better suited that way – not because Write-Back is buggy or unreliable. Chances are that Write-Back is not required, so we just save Flash capacity that way. So when you see this

Exadata storage indexes and DML

Last week I’ve gotten a question on how storage indexes (SI) behave when the table for which the SI is holding data is changed. Based on logical reasoning, it can be two things: the SI is invalidated because the data it’s holding is changed, or the SI is updated to reflect the change. Think about this for yourself, and pick a choice. I would love to hear if you did choose the correct one.

First let’s do a step back and lay some groundwork first. The tests done in this blogpost are done on an actual Exadata (V2 hardware), with Oracle version 11.2.0.4.6 (meaning bundle patch 6). The Exadata “cellos” (Cell O/S) version is 11.2.3.3.1.140529.1 on both the compute nodes and the storage nodes.

User Group Meetings Next Week (free training everyone!)

I know, posts about up-coming user group meetings are not exactly exciting, but it’s good to be reminded. You can’t beat a bit of free training, can you?

On Monday 14th I am doing a lightning talk at the 4th Oracle Midlands event. The main reason to come along is to see Jonathan Lewis talk about designing efficient SQL and then he will also do a 10 minute session on Breaking Exadata (to achieve that aim I suggest you just follow the advice of the Oracle Sales teams, that will break Exadata for you pretty efficiently!).

Why is P1 the only parameter populated in cell smart table scan?

Anyone who has looked at Exadata might ask the question, and I did so too. After all, cell smart table scan is in wait class User IO so there should be more, right? This is what you find for a smart scan:

NAME                           PARAMETER1           PARAMETER2           PARAMETER3                     WAIT_CLASS
------------------------------ -------------------- -------------------- ------------------------------ ---------------
cell smart table scan          cellhash#                                                                User I/O
cell smart index scan          cellhash#                                                                User I/O

Compare this to the traditional IO request:

Why does the Optimiser not respect my qb_name() hint?

I recently was involved in an investigation on a slow-running report on an Exadata system. This was rather interesting, the raw text file with the query was 33kb in size, and SQL Developer formatted the query to > 1000 lines. There were lots of interesting constructs in the query and the optimiser did its best to make sense of the inline views and various joins.

Reconstructing oratab from the cluster registry

At the Accenture Enkitec Group we have a couple of Exadata racks for Proof of Concepts (PoC), Performance validation, research and experimenting. This means the databases on the racks appear and vanish more than (should be) on an average customer Exadata rack (to be honest most people use a fixed few existing databases rather than creating and removing a database for every test).

Nevertheless we gotten in a situation where the /etc/oratab file was not in sync with the databases registered in the cluster registry. This situation can happen for a number reasons. For example, if you clone a database (RMAN duplicate), you end up with a cloned database (I sincerely hope), but this database needs to be manually registered in the cluster registry. This is the same with creating a standby database (for which one of the most used methods is to use the clone procedure with a couple of changes).

My SDU goes to 11 ^h^h I meant 2097152

One of the cool new things in 12.1 is that you can set the Session Data Unit to 2MB. This might not sound like a Big Deal, but getting this to work required me to dig deeper into the TNS layer than I intended…Then I somehow got stuck on the wrong track, thankfully the team at Enkitec helped out here with pointers.

This post is rather boring if you just look at it but it’s probably one of the best examples where a few sentences in writing are vastly different from the time it took to get to the bottom of it. The solution explained here works on our 12.1.0.1.3 Exadata lab system, which is an X2-2 but should likewise be applicable for other configurations.

The Server Setup

My SDU goes to 11 ^h^h I meant 2097152

One of the cool new things in 12.1 is that you can set the Session Data Unit to 2MB. This might not sound like a Big Deal, but getting this to work required me to dig deeper into the TNS layer than I intended…Then I somehow got stuck on the wrong track, thankfully the team at Enkitec helped out here with pointers.

This post is rather boring if you just look at it but it’s probably one of the best examples where a few sentences in writing are vastly different from the time it took to get to the bottom of it. The solution explained here works on our 12.1.0.1.3 Exadata lab system, which is an X2-2 but should likewise be applicable for other configurations.

The Server Setup

Combining Bloom Filter Offloading and Storage Indexes on Exadata

Here’s a little known feature of Exadata – you can use a Bloom filter computed from a join column of a table to skip disk I/Os against another table it is joined to. This not the same as the Bloom filtering of the datablock contents in Exadata storage cells, but rather avoiding reading in some storage regions from the disks completely.

So, you can use storage indexes to skip I/Os against your large fact table, based on a bloom filter calculated from a small dimension table!