Friday Nov 20, 2015

Questions You Asked: What happens to a table In-Memory if one of my RAC nodes goes down?

We’ve written a number of blog posts on how Database In-Memory behaves in a RAC environment but recently we’ve gotten a lot of questions regarding what happens if one of the RAC nodes should fail. So, I thought I would try tackle this question and point out a couple of other interesting aspects of running Database In-Memory on RAC in this post.

Quick Recap

If you recall from part 1 of our RAC series each RAC node has it’s own In-Memory column store (IM column store). When a table is populated into memory in a RAC environment it will be distributed across all of the IM column stores in the cluster. That is to say, a piece of the table will appear in each RAC node.

Let’s take a look at an example using the LINEORDER table, which has 5 million rows in it and is approximately 550MB in size on my 3 node RAC cluster.

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Friday Nov 13, 2015

Questions You Asked: When using interval partitioning, will new partitions be placed In-Memory?

This is the second in our series of "Questions You Asked" and this time the question has to do with interval partitioning and whether newly created partitions will be populated into the IM column store.

We'll begin our experiment by creating an interval partitioned table based on the SUPPLIER table from our SSB schema. I've added a key_no column to make the interval partitioning easy. We then insert data into three partitions and list the results. Note that the first partition is named p1 because we had to create at least one partition with our CREATE TABLE statement. The other two are system generated names and those partitions were created automatically as part of the interval partitioning feature when we ran the second and third insert statements as you can see below.

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Saturday Sep 12, 2015

Oracle Open World 2015 Time to plan your schedule!

There are only 6 weeks to go until Oracle Open World, the largest gathering of Oracle customers, partners, developers, and technology enthusiasts, which begins on October 25th in San Francisco.

Of course the In-Memory development group will be there and you will have multiple opportunities to meet up with us, in one of our technical sessions, our hands-on-labs or at the Oracle demogrounds.

This year the In-Memory team has 4 technical sessions and there are also 5 excellent customer sessions you shouldn't miss.

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Wednesday Aug 05, 2015

New White Paper on using Database In-Memory with the E-Business Suite Released!

We would like to draw your attention to a new white paper has just been released titled "Using Oracle Database In-Memory with Oracle E-Business Suite".

The white paper details how Database In-Memory works, what the requirements are to use it with the E-Business Suite and works through some use cases and examples.  More details can be found in the My Oracle Support (MOS) Note 2025309.1.

The EBS team worked on hard on this paper and we think it's a great source of information for E-Business customers who want to take advantage of Oracle Database In-Memory. Enjoy the read!

Tuesday Jul 21, 2015

Oracle Database In-Memory Bundle Patch 10 Released

The latest Bundle Patch for Database In-Memory has been released. The Bundle Patch is 21188742 or Bundle Patch 10 for Engineered Systems and DB In-Memory (July2015)). This Bundle Patch improves the performance of mixed workload environments (OLTP & DW workloads), as well as enhancing the performance of analytic queries with aggregation. More information on the latest Bundle Patch can be found in the MOS note 21188742.8 or in the Mos note: Bundle Patches for Engineered Systems and DB In-Memory (Doc ID 1937782.1).

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Friday Jul 10, 2015

Star Schema Challenge - Part 2.1

In Star Schema Challenge – Part 2 I revealed baseline results for my query workload running on a 500 million row star schema with all tables marked NO INMEMORY and In-Memory Aggregation prevented using the NO_VECTOR_TRANSFORM hint. With a median of 16.9 seconds per query (allowing for an average think time between queries of 5 seconds), I decided that 25 users were enough for a baseline.

After my first post in this series someone suggested that the best implementation might be a de-normalized table. I decided to satisfy this user’s curiosity and test a de-normalized table also, starting with NO INMEMORY test. (Vector Transform is not applicable to the de-normalized table because it does not join to another table.)

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Friday May 08, 2015

Getting started with Oracle Database In-Memory Part V - Controlling Access

I’m finally going to make good on a promise I made way back in part 3 of our getting started with In-Memory series, to explain how you could control which queries use the In-Memory column store (IM column store) and which don't.

As with all new query performances enhancing features in the Oracle Database, a number of initialization parameters and hints have been introduce that enable you to control when and how the IM column store will be used. This post provides information on the initialization parameter, while the details on the Optimizer hint that control the use of the IM column store can be found on the Optimizer blog.

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Friday Apr 17, 2015

CPU Efficient Query Processing with Database In-Memory

In my last post I talked about In-Memory Aggregation and mentioned that the vector transformation plan is more CPU efficient than alternative plans. In this post I’ll provide a few examples to illustrate just how effective a vector transformation plan can be.

Let’s consider a star schema, with one fact table and 9 dimension tables (time, customer, product, channel and demographic attributes such as age and income).

9 Dimensional Star

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Tuesday Mar 31, 2015

Push-Down: Making Queries Fast!

In our previous posts we discussed the basic architecture of the In-Memory column store (IM column store) and now we want to drill down into some of the unique performance enhancing features. Push-down is one of the optimizations that makes scanning columns in the IM column store very efficient. Oracle Database In-Memory has the ability to push predicates, aggregations and group-bys down into the scan of a column or columns.  This ability to push-down allows us to take advantage of other performance enhancing features of Database In-Memory like SIMD vector processing and storage indexes.

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Monday Feb 16, 2015

Getting started with Oracle Database In-Memory Part V - Aggregation

When most people think about Oracle Database In-Memory (Database In-Memory), the first thing that comes to mind is super fast scanning and filtering operations. But what you may not know is Database In-Memory also includes many SQL optimizations designed to accelerate star and snowflake type queries. We refer to this collection of SQL optimizations as In-Memory Aggregation (IMA). IMA is typically 3-10x faster than ‘conventional’ plans, and that’s in addition to the improvements provided by scanning and filtering the data via the In-Memory column store (IM column store).

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The Oracle Database In-Memory blog is written by the Oracle product management team and sheds light on all things In-Memory.


« November 2015