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A pretty recent summary article from Oracle on enabling and getting SQL monitoring reports in various ways (including historical captures):
Real-Time SQL Monitoring: a MUST for SQL Tuning
https://t.co/S749xeCO4U
(I'm working on something new & related too ;-)
New blog: "Get Oracle Partition High Values as VARCHAR2 types instead of LONG in Oracle 19c and earlier"
There's also some SQL "performance trap" advice & data 23/26ai data dictionary internals in there.
Link in comments (testing if it changes "reach" :-)
Get Oracle Partition High Values as VARCHAR2 types instead of LONG in Oracle 19c and earlier (new blog).
There's also some data 23/26ai data dictionary internals!
https://t.co/PIkyCLc4gJ
I wrote an Oracle "ash_index_helper.sql" script 5 yrs ago, trying to pull all relevant info of top time-consuming *access paths* into one place, as a single SQL script.
Summarize access paths to a schema or just one table/SQL.
Too complex for a single script, time for AI? 😎
Reasons why SELECT * is bad for SQL performance:
An old blog (with Oracle-specific examples) with a whole range of reasons why. It's not only about network traffic and SQL plan execution, but client side processing and memory usage as well.
https://t.co/6X5qhdpuFY
The first deep dive in my new special-focus training series starts on Wednesday:
"Handling the Optimizer, Statistics and Workloads on Partitioned Tables in Oracle Databases" (5-6 Nov 2025 + Q&A followup sessions).
One demo table has 100k partitions ;-)
Sign up here:
https://t.co/NmwgHaFr4C
Misconfigured control_file_record_keep_time=365 bloated the control file → RMAN vs LGWR contention on control file → log file sync spiked → RAC flooded with gc waits.
#oracle#oracleace#oracleaw
Filter tables on their partition key to get partition pruning in Oracle #SQL
=> your query is more efficient
But with reference partitioning, this key is in the parent table!
@davidmkurtz shows how filtering these by foreign key enables pruning
https://t.co/V3OYZy1YFM
parses 136/s + executes 226/s = 362, but user calls hit 4,133/s. The gap (≈3,771) comes from fetches—big result sets exceed arraysize, forcing multiple fetches. SQL*Net roundtrips confirm (≈3,968/s).
#oracle#oracleace#awr
The xCapture and xtop eBPF tools are now in beta, with a demo dataset!
With a pre-recorded xcapture dataset from my dev server, now you can play with xtop "thread activity sampling" drilldown even on your laptop, without having to run xcapture yourself!
(link in replies :-)
If you have eBPF "biolatency" style IO latency monitoring tools always-on, you might want to reduce its tracepoint CPU overhead by not storing IO start times in a shared hashtable at all.
In my results, 59x lower tracepoint CPU overhead at 37M IOPS 😎
https://t.co/wuQuTRILFG
Didn't realize that Oracle Cloud now also offers AMD CPU-based (small) compute VMs under their "always free" offering, in addition to the ARM ones:
https://t.co/7ZgQcKyald
Fresh video! Want to run MERGE in parallel for your massive partitioned tables? There is a little bit of nuance required to make sure you get the performance you want.
https://t.co/H8zZlKOZPV
To find rows matching a #SQL query, the Oracle optimizer can use
ACCESS - get all of a subset of rows (usually via an index)
FILTER - check a set of rows, discarding unwanted data
But how does it pick which to use?
@connor_mc_d investigates https://t.co/5kCWSVNheG