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February 2020

Demystifying JSON with CockroachDB… Import, Index, and Computed Columns

Overview

Recently, I created and delivered an "Advanced Developer Workshop" for CockroachLabs. One of the topics dove into how to ingest and use JSON data.

Like many databases, CockroachDB has the ability to use JSON data type for columns within a table. Basically, you insert a JSONB object into a row, and then can filter and extract the desired data with SQL. The following simple example shows how this is done:

So it is pretty straight forward to use JSONB objects within tables, but how do you load those HUGE json files into CockroachDB?

Bug Bounty

There has been a rise on bug bounty programs and websites that help researchers find and disclose bugs to website and other owners with the hope of a payout from the owner of the vulnerable wesbsites. Some big well known....[Read More]

Posted by Pete On 11/02/20 At 10:09 AM

Video : Oracle : Silent Installation and Database Creation

In today’s video we’ll take a look at the two sections of a database build that people often use a GUI for. The software installation using the Oracle Universal Installer (OUI), and the database creation using the Database Configuration Assistant (DBCA).

GROUP BY might be distinctly better than DISTINCT

One of the cool things with materialised* views in Oracle is their ability to be kept in sync with the source table(s) from which they are derived from, in real time or near real time. To achieve this, we typically employ mechanisms such as materialised view logs to capture modifications to the source tables, and occasionally we need to change the definition of the materialised view itself when dealing with aggregations and joins. However, some times we know that if DML on the source is incredibly rare and/or the cost of updating the materialised view is very small, we can avoid all that and simply perform a REFRESH COMPLETE whenever a transaction is committed on the source tables. This avoids any issue around the materialised view becoming stale, and also avoids the need for scheduler jobs to keep the materialised view refreshed.

Oracle Performance Troubleshooting Without OS Access, Part 1: Identifying CPU Scheduling Latency

As running Oracle databases as (partially) managed services in the cloud has become quite popular, I thought to start a little series about troubleshooting Oracle (performance) stuff when not having OS access. This will help with such cloud services, but also in cases where your team just doesn’t have convenient OS access due to some separation of privileges reasons.
The first example is my schedlat.sql script that uses X$KSO_SCHED_DELAY_HISTORY to list sampled process scheduling latency details with a 15 minute history.

Oracle Performance Troubleshooting Without OS Access, Part 1: Identifying CPU Scheduling Latency

As running Oracle databases as (partially) managed services in the cloud has become quite popular, I thought to start a little series about troubleshooting Oracle (performance) stuff when not having OS access. This will help with such cloud services, but also in cases where your team just doesn’t have convenient OS access due to some separation of privileges reasons.
The first example is my schedlat.sql script that uses X$KSO_SCHED_DELAY_HISTORY to list sampled process scheduling latency details with a 15 minute history.

Vagrant 2.2.7

Over the weekend I noticed Vagrant 2.2.7 had been released. It came out at the end of January, but I guess most of the time I just start a build and look at something else until it completes, so I didn’t see the glaringly obvious message telling me about the update. </p />
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Understanding as a Flawed Ally How We All Can be Better

It was brought to my ADHD attention, that one of our community members is leaving after she was made to feel unwelcome by some who, (IMHO) have insecurities so deep, that they have nothing else better to do than do harm to others.

How SQL Server MVCC compares to Oracle and PostgreSQL

By Franck Pachot

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Microsoft SQL Server has implemented MVCC in 2005, which has been proven to be the best approach for transaction isolation (the I in ACID) in OLTP. But are you sure that writers do not block readers with READ_COMMITTED_SNAPSHOT? I’ll show here that some reads are still blocked by locked rows, contrary to the precursors of MVCC like PostgreSQL and Oracle.

For this demo, I run SQL Server 2019 RHEL image on docker in an Oracle Cloud compute running OEL7.7 as explained in the previous post. If you don’t have the memory limit mentioned, you can simply run:

docker run -d -e "ACCEPT_EULA=Y" -e 'MSSQL_PID=Express' -p 1433:1433 -e 'SA_PASSWORD=**P455w0rd**' --name mssql mcr.microsoft.com/mssql/rhel/server:2019-latest