Share this
Batched table access
by Timur Akhmadeev on Nov 29, 2013 12:00:00 AM
Intro
Here is what I'm talking about: [sourcecode lang="sql" highlight="5"] ------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1000 | 990K| 148 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID BATCHED| T1 | 1000 | 990K| 148 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | T1_Y_INDX | 1000 | | 5 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 2 - access("Y"=TO_NUMBER(:1)) [/sourcecode] Line 1 of this very simple execution plan shows how Oracle 12c added a suffix BATCHED to the table access by a B*Tree index rowsource. I was thinking about the reasons behind this change and how it could be implemented before starting my tests. Why Oracle would want to "batch" table access Usually large index range/full/skip scans with subsequent table access running serially cause lots of single block reads of a table. Depending on the clustering of the data, the number of table block reads could be as high as the number of ROWIDs fetched from index leaf blocks up to the next rowsource. In case of a serial execution plan it means that query performance depends on how fast single random table read is. Say you need to read 1000 random table blocks located far away from each other and average read of 1 block takes 5ms, then you need about 5 seconds to execute such query. But if the storage subsystem can handle concurrent IO requests well enough, and you were able to ask it for 1000 blocks someway concurrently or in parallel, transparent for the end user session, then it could take less wall clock time for a user while putting more pressure on the OS, storage and connectivity to the storage. How Oracle optimizes IO already As far as I know, Oracle can and does a few cunning things with IO even in pre-12.1 releases. Here is a(n incomplete, most likely) list with example optimizations you may see:- Within NESTED LOOP joins there are couple of strategies Oracle uses: NL-join batching and moving TABLE ACCESS out of a join (I've no idea how it is called exactly).
- "Prefetching" with 'db file parallel read' - as described by Tanel Poder here (it gives you a very nice idea of what 'db file parallel read's are)
- In case of a "cold" buffer cache Oracle may choose to read ahead, and instead of reading just a single block when you think it is enough, Oracle may opt to reading multiple physically adjacent on disk blocks to the cache (aka 'db file scattered read'). Sometimes it could hurt (a lot) the application performance, sometimes it doesn't matter, but the thing is: it's a "normal" thing to experience multi-block buffered reads on what should probably be single block reads.
Test Case
Based on my understanding of what Oracle can possibly do I have created a test scenario which could be used to find out more things behind BATCHED table access. Here is the setup: [sourcecode lang="sql"] drop table t1 cascade constraints purge; create table t1 ( id integer, x integer, y integer, pad varchar2(4000) ); insert /*+ append */ into t1 select rownum, mod(rownum, 1000), floor((rownum-1)/1000), lpad('x', 1000, 'x') from all_source a1, all_source a2 where rownum <= 1e6; create index t1_x_indx on t1(x); create index t1_y_indx on t1(y); exec dbms_stats.gather_table_stats(user, 't1', method_opt=>'for all columns size 1', cascade=>true, no_invalidate=>false); [/sourcecode] Very easy. I have created a sufficiently wide table holding 1 million rows with two integer columns following a very bad (T1.X) and very good (T1.Y) clustering of data. Usually it is also important where are you creating this table. Initially I created it in a standard USERS tablespace (i.e., ASSM, non-uniform extent size), but then switched to a MSSM tablespace with uniform extents of 1MB. Looking ahead, it does not make a difference to the test results (at least I could not identify it.) The test itself: [sourcecode lang="sql"] set linesize 180 pagesize 100 define ^ arraysize 100 col plan_table_output format a180 explain plan for select /*+ index(t1(x)) */ * from t1 where x = :1; select * from table(dbms_xplan.display); explain plan for select /*+ index(t1(y)) */ * from t1 where y = :1; select * from table(dbms_xplan.display); col spid new_value spid col curr_date new_value curr_date select p.spid,to_char(sysdate, 'YYYYMMDDHH24MI') curr_date from v$session s, v$process p where s.paddr = p.addr and s.sid = userenv('sid'); col tracefile new_value tracefile select value tracefile from v$diag_info where name='Default Trace File'; alter system flush buffer_cache; !sleep 1 alter system flush buffer_cache; select object_id, data_object_id, object_name from dba_objects where owner = user and object_name like 'T1%'; set termout off exec dbms_session.session_trace_enable(waits=>true, binds=>false) !strace -tt -p ^spid -o trc_^spid..txt & spool batched_^curr_date..txt select /*+ index(t1(x)) */ * from t1 where x = 1; select /*+ index(t1(y)) */ * from t1 where y = 2; spool off set termout on !orasrp -t --sort=fchela --sys=no ^tracefile orasrp_^spid..txt !cat orasrp_^spid..txt | grep -A 165 fvkg1sp2b73x prompt trace: orasrp_^spid..txt prompt strace: trc_^spid..txt prompt tracefile: ^tracefile exit [/sourcecode] So the test is also really easy, except for some diagnostic & preparation steps. Basically I'm tracing two statements, which are accessing T1 by two indexes respectively, both at OS and Oracle levels, and then parse Oracle trace file with OraSRP. You may want to use tkprof. I also used it initially but OraSRP has one feature which helps to see the waits with breakdown by object, like this: [sourcecode] --------- Time Per Call -------- Object/Event % Time Seconds Calls Avg Min Max -------------------------------------------- -------- ------------ --------- ---------- ---------- ---------- TABLE T1 [88650] db file parallel read 68.9% 4.8404s 26 0.1862s 0.0883s 0.2614s db file sequential read 29.9% 2.1023s 147 0.0143s 0.0014s 0.0636s INDEX T1_X_INDX [88651] db file sequential read 1.1% 0.0746s 5 0.0149s 0.0025s 0.0278s Disk file operations I/O 0.0% 0.0034s 1 0.0034s 0.0034s 0.0034s [/sourcecode]Testing
I was using VirtualBox with 64-bit OEL 6.4 and Oracle 11.2.0.4 & 12.1.0.1. I also did (partial) tests on 11.2.0.3 running in OVM on a faster storage, and the results were similar to what I've observed with 11.2.0.4. Both instances were running with a pfile, with following parameters specified: [sourcecode] -- 11.2.0.4 *._db_cache_pre_warm=FALSE *.compatible='11.2.0.4.0' *.control_files='/u01/app/oracle/oradata/ora11204/control01.ctl','/u01/app/oracle/fast_recovery_area/ora11204/control02.ctl' *.db_block_size=8192 *.db_cache_size=300000000 *.db_domain='' *.db_name='ora11204' *.diagnostic_dest='/u01/app/oracle' *.dispatchers='(PROTOCOL=TCP) (SERVICE=ora11204XDB)' *.filesystemio_options=setall *.pga_aggregate_target=100000000 *.open_cursors=300 *.processes=100 *.remote_login_passwordfile='EXCLUSIVE' *.shared_pool_size=420430400 *.undo_tablespace='UNDOTBS1' -- 12.1.0.1 *._db_cache_pre_warm=FALSE *.compatible='12.1.0.0.0' *.control_files='/u01/app/oracle/oradata/ora121/control01.ctl','/u01/app/oracle/oradata/ora121/control02.ctl' *.db_block_size=8192 *.db_cache_size=300000000 *.db_domain='' *.db_name='ora121' *.diagnostic_dest='/u01/app/oracle' *.dispatchers='(PROTOCOL=TCP) (SERVICE=ora121XDB)' *.enable_pluggable_database=true *.filesystemio_options='SETALL' *.pga_aggregate_target=100000000 *.open_cursors=300 *.processes=100 *.remote_login_passwordfile='EXCLUSIVE' *.shared_pool_size=420430400 *.undo_tablespace='UNDOTBS1' [/sourcecode]Test Process & Observations
Initially I started testing with a default database config, and filesystemio_options set to DIRECTIO. After some random tests, I realized that this cache warm up thing is not what I'm interested in right now and turned it off with a hidden parameter. Overall I think that the test results could be explained in the following:- Test results are inconsistent. This is the most irritating thing. However, after I ran the test multiple times in a row, I get a pretty stable outcome. So I consider the results after multiple consecutive runs of the same test. Usually it is just 2 runs, but sometimes more, especially after an instance restart. I've no understanding why it happens and what's behind the scene of the decisions. Maybe it has something to do with CKPT as Tanel mentions in his post on oracle-l, but I did not check (and honestly don't want to :))
- Both 11g and 12c show that for a table access of scattered data (by T1_X_INDX index) Oracle may batch table access IO using db file parallel reads; on the OS level it is using io_submit/io_getevents calls to run IO with async API if it's turned on of course; in case of just DIRECTIO in place it uses a bunch of single block reads using pread
- Both 11g and 12c can use multi-block access of clustered data (by T1_Y_INDX index) for index range scans (and most likely, full/skip scans too). This is one of the most amusing things: even though I turned off cache warm up, Oracle still can identify that the data I am accessing is well placed altogether, and it decides to read multiple adjacent table blocks at once. 12c, However, behaves differently and by default does not use buffered multi-block table reads
- The size of multi-block IO (db file parallel read) is different between 11g and 12c: in 11g it is usually 39, sometimes 19. With 12c, by default the number of requests depends on the client's fetch size: it is equal to the minimum of fetch size and 127
- Looks like the parameter _db_file_noncontig_mblock_read_count does not control the actual number of blocks read with db file parallel read; any value greater than 1 turns this feature on and the size of read requests stays the same (I have tested only setting it to 1, 2, 3, 5)
- The word BATCHED appeared in execution plans of 12c is controlled with a new hidden parameter _optimizer_batch_table_access_by_rowid. By default the parameter is set to TRUE, so plans tend to include BATCHED in table access rowsource. In the run-time this setting acts very much similar to 11g behavior, so it reads scattered table data with db file parallel reads, except for the number of IO requests which is min(fetch_size, 127). If _optimizer_batch_table_access_by_rowid is set to FALSE on a session level, for example, then the plans generated by Oracle do not include BATCHED suffix in table access rowsource, but in run-time Oracle still uses multi-block IO in the same way as 11g does, i.e. 39 or 19 IO requests per one call and scattered reads of clustered table data are there as well!
Summary
In 12c Oracle changed some internal code path which deals with the batched table access. But important thing is that the batched table access is not new, so even if you disable it either explicitly with _optimizer_batch_table_access_by_rowid or implicitly with optimizer_features_enable, Oracle will still be able to utilize a similar approach as it was in 11g. One important thing, of course, is that by default the size of vector IO now depends on the client fetch size. And I can imagine a situation in which this change could make an impact on the application performance after an upgrade. I have uploaded test script & trace files from 11.2.0.4 and 12.1.0.1 here so if you would like to repeat my tests and compare results - feel free to do that.Share this
- Technical Track (967)
- Oracle (409)
- MySQL (140)
- Cloud (128)
- Microsoft SQL Server (117)
- Open Source (90)
- Google Cloud (81)
- DBA Lounge (76)
- Technical Blog (74)
- Microsoft Azure (63)
- Amazon Web Services (AWS) (58)
- Big Data (52)
- Google Cloud Platform (46)
- Cassandra (44)
- DevOps (41)
- Pythian (33)
- Linux (30)
- Database (26)
- Podcasts (25)
- Site Reliability Engineering (25)
- Performance (24)
- PostgreSQL (24)
- Oracle E-Business Suite (23)
- Oracle Database (22)
- Docker (21)
- Group Blog Posts (20)
- Security (20)
- DBA (19)
- Log Buffer (19)
- Exadata (18)
- MongoDB (18)
- Oracle Cloud Infrastructure (OCI) (18)
- Oracle Exadata (18)
- Automation (17)
- Hadoop (16)
- Oracleebs (16)
- Amazon RDS (15)
- Ansible (15)
- Ebs (15)
- Snowflake (15)
- ASM (13)
- BigQuery (13)
- Patching (13)
- RDS (13)
- Replication (13)
- Advanced Analytics (12)
- Artificial Intelligence (AI) (12)
- Data (12)
- GenAI (12)
- Kubernetes (12)
- LLM (12)
- Authentication, SSO and MFA (11)
- Backup (11)
- Cloud Migration (11)
- Machine Learning (11)
- OCI (11)
- Rman (11)
- Datascape Podcast (10)
- Monitoring (10)
- R12 (10)
- Apache Cassandra (9)
- ChatGPT (9)
- Data Guard (9)
- Infrastructure (9)
- Oracle Applications (9)
- Python (9)
- Series (9)
- AWR (8)
- Articles (8)
- High Availability (8)
- Oracle EBS (8)
- Oracle Enterprise Manager (OEM) (8)
- Percona (8)
- Powershell (8)
- Recovery (8)
- Weblogic (8)
- Apache Beam (7)
- Backups (7)
- Data Governance (7)
- Goldengate (7)
- Innodb (7)
- Microsoft Azure SQL Database (7)
- Migration (7)
- Myrocks (7)
- OEM (7)
- Performance Tuning (7)
- Data Enablement (6)
- Data Visualization (6)
- Database Performance (6)
- E-Business Suite (6)
- Fmw (6)
- Grafana (6)
- Oracle Enterprise Manager (6)
- Orchestrator (6)
- Rac (6)
- Renew Refresh Republish (6)
- RocksDB (6)
- Serverless (6)
- Upgrade (6)
- Azure Data Factory (5)
- Azure Synapse Analytics (5)
- Covid-19 (5)
- Cpu (5)
- Disaster Recovery (5)
- Error (5)
- Generative AI (5)
- Google BigQuery (5)
- Indexes (5)
- Love Letters To Data (5)
- Mariadb (5)
- Microsoft (5)
- Proxysql (5)
- Scala (5)
- VMware (5)
- Windows (5)
- Xtrabackup (5)
- Airflow (4)
- Analytics (4)
- Apex (4)
- Best Practices (4)
- Centrally Managed Users (4)
- Cli (4)
- Cloud Security (4)
- Cloud Spanner (4)
- CockroachDB (4)
- Configuration Management (4)
- Container (4)
- Data Management (4)
- Data Pipeline (4)
- Data Security (4)
- Data Strategy (4)
- Database Administrator (4)
- Database Management (4)
- Database Migration (4)
- Dataflow (4)
- Dbsat (4)
- Elasticsearch (4)
- Fahd Mirza (4)
- Fusion Middleware (4)
- Google (4)
- Io (4)
- Java (4)
- Kafka (4)
- Middleware (4)
- Network (4)
- Ocidtab (4)
- Opatch (4)
- Oracle Autonomous Database (Adb) (4)
- Oracle Cloud (4)
- Pitr (4)
- Post-Mortem Analysis (4)
- Prometheus (4)
- Redhat (4)
- Slob (4)
- Ssl (4)
- Terraform (4)
- Workflow (4)
- Amazon Relational Database Service (Rds) (3)
- Apache Kafka (3)
- Apexexport (3)
- Aurora (3)
- Business Intelligence (3)
- Cdb (3)
- Cloud Armor (3)
- Cloud Database (3)
- Cloud FinOps (3)
- Cluster (3)
- Consul (3)
- Cosmos Db (3)
- Crontab (3)
- Data Analytics (3)
- Data Integration (3)
- Database Monitoring (3)
- Database Troubleshooting (3)
- Database Upgrade (3)
- Databases (3)
- Dataops (3)
- Dbt (3)
- Digital Transformation (3)
- ERP (3)
- Google Chrome (3)
- Google Cloud Sql (3)
- Google Workspace (3)
- Graphite (3)
- Haproxy (3)
- Heterogeneous Database Migration (3)
- Hugepages (3)
- Inside Pythian (3)
- Installation (3)
- Json (3)
- Keras (3)
- Ldap (3)
- Liquibase (3)
- Love Letter (3)
- Lua (3)
- Mfa (3)
- Multitenant (3)
- Nginx (3)
- Nodetool (3)
- Oem 13C (3)
- Oms (3)
- Omspatcher (3)
- Oracle Data Guard (3)
- Oracle Live Sql (3)
- Oracle Rac (3)
- Patch (3)
- Perl (3)
- Pmm (3)
- Pt-Online-Schema-Change (3)
- Rdbms (3)
- Recommended (3)
- Remote Teams (3)
- Reporting (3)
- Reverse Proxy (3)
- S3 (3)
- SAP (3)
- Spark (3)
- Ssis (3)
- Ssis Catalog (3)
- Striim (3)
- Sysadmin (3)
- System Versioned (3)
- Systemd (3)
- Temporal Tables (3)
- Tensorflow (3)
- Tools (3)
- Tuning (3)
- Vault (3)
- Vulnerability (3)
- Waf (3)
- Adf (2)
- Adop (2)
- Agent (2)
- Agile (2)
- Amazon Data Migration Service (2)
- Amazon Ec2 (2)
- Amazon S3 (2)
- Apache Flink (2)
- Apple (2)
- Apps (2)
- Ashdump (2)
- Atp (2)
- Autonomous (2)
- Awr Data Mining (2)
- Bash (2)
- Business (2)
- Caching (2)
- Cdap (2)
- Cloning (2)
- Cloud Cost Optimization (2)
- Cloud Data Fusion (2)
- Cloud Hosting (2)
- Cloud Infrastructure (2)
- Cloud Shell (2)
- Cloud Sql (2)
- Cloudscape (2)
- Cluster Level Consistency (2)
- Conferences (2)
- Consul-Template (2)
- Containerization (2)
- Containers (2)
- Cosmosdb (2)
- Cost Management (2)
- Costs (2)
- Cql (2)
- Cqlsh (2)
- Cyber Security (2)
- Data Analysis (2)
- Data Discovery (2)
- Data Engineering (2)
- Data Migration (2)
- Data Modeling (2)
- Data Quality (2)
- Data Streaming (2)
- Data Warehouse (2)
- Database Consulting (2)
- Database Migrations (2)
- Dataguard (2)
- Datapump (2)
- Ddl (2)
- Debezium (2)
- Dictionary Views (2)
- Dms (2)
- Docker-Composer (2)
- Dr (2)
- Duplicate (2)
- Ecc (2)
- Elastic (2)
- Elastic Stack (2)
- Em12C (2)
- Encryption (2)
- Enterprise Data Platform (EDP) (2)
- Enterprise Manager (2)
- Etl (2)
- Events (2)
- Exachk (2)
- Filter Driver (2)
- Flume (2)
- Full Text Search (2)
- Galera (2)
- Gemini (2)
- General Purpose Ssd (2)
- Gh-Ost (2)
- Gke (2)
- Hanganalyze (2)
- Hdfs (2)
- Health Check (2)
- Historical Trends (2)
- Incremental (2)
- Infiniband (2)
- Infrastructure As Code (2)
- Innodb Cluster (2)
- Innodb File Structure (2)
- Innodb Group Replication (2)
- Install (2)
- Internals (2)
- Java Web Start (2)
- Kibana (2)
- Log (2)
- Log4J (2)
- Logs (2)
- Memory (2)
- Merge Replication (2)
- Metrics (2)
- Mutex (2)
- NLP (2)
- Neo4J (2)
- Node.Js (2)
- Nosql (2)
- Ntp (2)
- Oci Iam (2)
- Oem12C (2)
- Opatchauto (2)
- Open Source Database (2)
- Operational Excellence (2)
- Oracle Datase (2)
- Oracle Extended Manager (Oem) (2)
- Oracle Flashback (2)
- Oracle Forms (2)
- Oracle Installation (2)
- Oracle Io Testing (2)
- Pdb (2)
- Podcast (2)
- Power Bi (2)
- Puppet (2)
- R12.2 (2)
- Redshift (2)
- Remote DBA (2)
- Remote Sre (2)
- SAP HANA Cloud (2)
- Scale (2)
- Schema (2)
- Shell (2)
- Simon Pane (2)
- Single Sign-On (2)
- Sre (2)
- Ssis Catalog Error (2)
- Ssisdb (2)
- Standby (2)
- Statspack Mining (2)
- Systemstate Dump (2)
- Tablespace (2)
- Technical Training (2)
- Tempdb (2)
- Tfa (2)
- Throughput (2)
- Tls (2)
- Tombstones (2)
- Transactional Replication (2)
- Vagrant (2)
- Variables (2)
- Virtual Machine (2)
- Virtual Machines (2)
- Virtualbox (2)
- Web Application Firewall (2)
- Webinars (2)
- X5 (2)
- scalability (2)
- Actifio (1)
- Active Directory (1)
- Adaptive Hash Index (1)
- Adf Custom Email (1)
- Adrci (1)
- Advanced Data Services (1)
- Afd (1)
- After Logon Trigger (1)
- Ahf (1)
- Alloydb (1)
- Amazon (1)
- Amazon Athena (1)
- Amazon Aurora Backtrack (1)
- Amazon Efs (1)
- Amazon Redshift (1)
- Amazon Sagemaker (1)
- Amazon Vpc Flow Logs (1)
- Amdu (1)
- Analysis (1)
- Analytical Models (1)
- Analyzing Bigquery Via Sheets (1)
- Anisble (1)
- Anthos (1)
- Apache (1)
- Apache Nifi (1)
- Apache Spark (1)
- Application Migration (1)
- Architect (1)
- Architecture (1)
- Ash (1)
- Asmlib (1)
- Atlas CLI (1)
- Awr Mining (1)
- Aws Lake Formation (1)
- Azure Data Lake (1)
- Azure Data Lake Analytics (1)
- Azure Data Lake Store (1)
- Azure Data Migration Service (1)
- Azure OpenAI (1)
- Azure Sql Data Warehouse (1)
- Backup For Sql Server (1)
- Bacpac (1)
- Bag (1)
- Bare Metal Solution (1)
- Batch Operation (1)
- Batches In Cassandra (1)
- Beats (1)
- Best Practice (1)
- Bi Publisher (1)
- Binary Logging (1)
- Bind Variables (1)
- Bitnami (1)
- Blob Storage Endpoint (1)
- Blockchain (1)
- Browsers (1)
- Btp Architecture (1)
- Btp Components (1)
- Buffer Pool (1)
- Build 2019 Updates (1)
- Bundle Patch (1)
- Bushy Join (1)
- Business Continuity (1)
- Business Insights (1)
- Business Process Modelling (1)
- Business Reputation (1)
- CAPEX (1)
- Capacity Planning (1)
- Catcon.Pm (1)
- Catctl.Pl (1)
- Catupgrd.Sql (1)
- Cbo (1)
- Cdb Duplication (1)
- Chaos Engineering (1)
- Cheatsheet (1)
- Checkactivefilesandexecutables (1)
- Chmod (1)
- Chown (1)
- Chrome Enterprise (1)
- Chrome Security (1)
- Cl-Series (1)
- Cleanup (1)
- Cloud Browser (1)
- Cloud Build (1)
- Cloud Consulting (1)
- Cloud Data Warehouse (1)
- Cloud Database Management (1)
- Cloud Dataproc (1)
- Cloud Foundry (1)
- Cloud Manager (1)
- Cloud Networking (1)
- Cloud SQL Replica (1)
- Cloud Scheduler (1)
- Cloud Services (1)
- Cloud Strategies (1)
- Cloudformation (1)
- Cluster Resource (1)
- Cmo (1)
- Coding Benchmarks (1)
- Colab (1)
- Collectd (1)
- Columnar (1)
- Communication Plans (1)
- Community (1)
- Compact Storage (1)
- Compaction (1)
- Compliance (1)
- Compression (1)
- Compute Instances (1)
- Compute Node (1)
- Concurrent Manager (1)
- Concurrent Processing (1)
- Configuration (1)
- Consistency Level (1)
- Consolidation (1)
- Conversational AI (1)
- Cpu Patching (1)
- Cqlsstablewriter (1)
- Crash (1)
- Create Catalog Error (1)
- Create_File_Dest (1)
- Credentials (1)
- Cross Platform (1)
- CrowdStrike (1)
- Crsctl (1)
- Custom Instance Images (1)
- Cve-2022-21500 (1)
- Cvu (1)
- Cypher Queries (1)
- DAX (1)
- DBSAT 3 (1)
- Dacpac (1)
- Dag (1)
- Data Analytics Platform (1)
- Data Box (1)
- Data Classification (1)
- Data Cleansing (1)
- Data Encryption (1)
- Data Estate (1)
- Data Flow Management (1)
- Data Insights (1)
- Data Integrity (1)
- Data Lake (1)
- Data Leader (1)
- Data Lifecycle Management (1)
- Data Lineage (1)
- Data Masking (1)
- Data Mesh (1)
- Data Migration Assistant (1)
- Data Migration Service (1)
- Data Mining (1)
- Data Monetization (1)
- Data Policy (1)
- Data Profiling (1)
- Data Protection (1)
- Data Retention (1)
- Data Safe (1)
- Data Sheets (1)
- Data Summit (1)
- Data Vault (1)
- Data Warehouse Modernization (1)
- Database Auditing (1)
- Database Consultant (1)
- Database Link (1)
- Database Modernization (1)
- Database Provisioning (1)
- Database Provisioning Failed (1)
- Database Replication (1)
- Database Scaling (1)
- Database Schemas (1)
- Database Security (1)
- Databricks (1)
- Datadog (1)
- Datafile (1)
- Datapatch (1)
- Dataprivacy (1)
- Datascape 59 (1)
- Datasets (1)
- Datastax Opscenter (1)
- Datasync Error (1)
- Db_Create_File_Dest (1)
- Dbaas (1)
- Dbatools (1)
- Dbcc Checkident (1)
- Dbms_Cloud (1)
- Dbms_File_Transfer (1)
- Dbms_Metadata (1)
- Dbms_Service (1)
- Dbms_Stats (1)
- Dbupgrade (1)
- Deep Learning (1)
- DeepSeek (1)
- Delivery (1)
- Devd (1)
- Dgbroker (1)
- Dialogflow (1)
- Dict0Dict (1)
- Did You Know (1)
- Direct Path Read Temp (1)
- Disk Groups (1)
- Disk Management (1)
- Diskgroup (1)
- Dispatchers (1)
- Distributed Ag (1)
- Distribution Agent (1)
- Documentation (1)
- Download (1)
- Dp Agent (1)
- Duet AI (1)
- Duplication (1)
- Dynamic Sampling (1)
- Dynamic Tasks (1)
- E-Business Suite Cpu Patching (1)
- E-Business Suite Patching (1)
- Ebs Sso (1)
- Ec2 (1)
- Editions (1)
- Edp (1)
- El Carro (1)
- Elassandra (1)
- Elk Stack (1)
- Em13Cr2 (1)
- Emcli (1)
- End of Life (1)
- Engineering (1)
- Enqueue (1)
- Enterprise (1)
- Enterprise Architecture (1)
- Enterprise Command Centers (1)
- Enterprise Manager Command Line Interface (Em Cli (1)
- Enterprise Plus (1)
- Episode 58 (1)
- Error Handling (1)
- Exacc (1)
- Exacheck (1)
- Exacs (1)
- Exadata Asr (1)
- Execution (1)
- Executive Sponsor (1)
- Expenditure (1)
- Export Sccm Collection To Csv (1)
- External Persistent Volumes (1)
- Fail (1)
- Failed Upgrade (1)
- Fall 2021 (1)
- Fast Recovery Area (1)
- Flash Recovery Area (1)
- Flashback (1)
- Fnd (1)
- Fndsm (1)
- Force_Matching_Signature (1)
- Fra Full (1)
- Framework (1)
- Freebsd (1)
- Fsync (1)
- Function-Based Index (1)
- GCVE Architecture (1)
- GPQA (1)
- Gaming (1)
- Garbagecollect (1)
- Gcp Compute (1)
- Gcp-Spanner (1)
- Geography (1)
- Geth (1)
- Getmospatch (1)
- Git (1)
- Global Analytics (1)
- Google Analytics (1)
- Google Cloud Architecture Framework (1)
- Google Cloud Data Services (1)
- Google Cloud Partner (1)
- Google Cloud Spanner (1)
- Google Cloud VMware Engine (1)
- Google Compute Engine (1)
- Google Dataflow (1)
- Google Datalab (1)
- Google Grab And Go (1)
- Gp2 (1)
- Graph Algorithms (1)
- Graph Databases (1)
- Graph Inferences (1)
- Graph Theory (1)
- GraphQL (1)
- Graphical User Interface (Gui) (1)
- Grid (1)
- Grid Infrastructure (1)
- Griddisk Resize (1)
- Grp (1)
- Guaranteed Restore Point (1)
- Guid Mismatch (1)
- HR Technology (1)
- HRM (1)
- Ha (1)
- Hang (1)
- Hashicorp (1)
- Hbase (1)
- Hcc (1)
- Hdinsight (1)
- Healthcheck (1)
- Hemantgiri S. Goswami (1)
- Hortonworks (1)
- How To Install Ssrs (1)
- Hr (1)
- Httpchk (1)
- Https (1)
- Huge Pages (1)
- HumanEval (1)
- Hung Database (1)
- Hybrid Columnar Compression (1)
- Hyper-V (1)
- Hyperscale (1)
- Hypothesis Driven Development (1)
- Ibm (1)
- Identity Management (1)
- Idm (1)
- Ilom (1)
- Imageinfo (1)
- Impdp (1)
- In Place Upgrade (1)
- Incident Response (1)
- Indempotent (1)
- Influxdb (1)
- Information (1)
- Infrastructure As A Code (1)
- Injection (1)
- Innobackupex (1)
- Innodb Concurrency (1)
- Innodb Flush Method (1)
- Insights (1)
- Installing (1)
- Instance Cloning (1)
- Integration Services (1)
- Integrations (1)
- Interactive_Timeout (1)
- Interval Partitioning (1)
- Invisible Indexes (1)
- Io1 (1)
- IoT (1)
- Iops (1)
- Iphone (1)
- Ipv6 (1)
- Iscsi (1)
- Iscsi-Initiator-Utils (1)
- Iscsiadm (1)
- Issues (1)
- It Industry (1)
- It Teams (1)
- JMX Metrics (1)
- Jared Still (1)
- Javascript (1)
- Jdbc (1)
- Jinja2 (1)
- Jmx (1)
- Jmx Monitoring (1)
- Jvm (1)
- Jython (1)
- K8S (1)
- Kernel (1)
- Key Btp Components (1)
- Kfed (1)
- Kill Sessions (1)
- Knapsack (1)
- Kubeflow (1)
- LMSYS Chatbot Arena (1)
- Large Pages (1)
- Latency (1)
- Latest News (1)
- Leadership (1)
- Leap Second (1)
- Limits (1)
- Line 1 (1)
- Linkcolumn (1)
- Linux Host Monitoring (1)
- Linux Storage Appliance (1)
- Listener (1)
- Loadavg (1)
- Lock_Sga (1)
- Locks (1)
- Log File Switch (Archiving Needed) (1)
- Logfile (1)
- Looker (1)
- Lvm (1)
- MMLU (1)
- Managed Instance (1)
- Managed Services (1)
- Management (1)
- Management Servers (1)
- Marketing (1)
- Marketing Analytics (1)
- Martech (1)
- Masking (1)
- Megha Bedi (1)
- Metadata (1)
- Method-R Workbench (1)
- Metric (1)
- Metric Extensions (1)
- Michelle Gutzait (1)
- Microservices (1)
- Migrate (1)
- Migrating Ssis Catalog (1)
- Migration Checklist (1)
- Mirroring (1)
- Model Governance (1)
- Monetization (1)
- MongoDB Atlas (1)
- MongoDB Compass (1)
- Msdtc (1)
- Msdtc In Always On (1)
- Msdtc In Cluster (1)
- Multi-IP (1)
- Multicast (1)
- Multipath (1)
- My.Cnf (1)
- Nagios (1)
- Ndb (1)
- Net_Read_Timeout (1)
- Net_Write_Timeout (1)
- Netcat (1)
- Newsroom (1)
- Nfs (1)
- Nifi (1)
- Node (1)
- Null Columns (1)
- Nullipotent (1)
- OPEX (1)
- ORAPKI (1)
- O_Direct (1)
- Oacore (1)
- Oda (1)
- Odbcs (1)
- Odbs (1)
- Odi (1)
- Oel (1)
- Ohs (1)
- Olvm (1)
- On-Premises (1)
- Onclick (1)
- Open.Canada.Ca (1)
- Openstack (1)
- Operating System Monitoring (1)
- Oplog (1)
- Opsworks (1)
- Optimization (1)
- Optimizer (1)
- Ora-01852 (1)
- Ora-7445 (1)
- Oracle Cursor (1)
- Oracle Database Appliance (1)
- Oracle Database Se2 (1)
- Oracle Database Standard Edition 2 (1)
- Oracle Database Upgrade (1)
- Oracle Database@Google Cloud (1)
- Oracle Exadata Smart Scan (1)
- Oracle Licensing (1)
- Oracle Linux Virtualization Manager (1)
- Oracle Oda (1)
- Oracle Openworld (1)
- Oracle Parallelism (1)
- Oracle Rdbms (1)
- Oracle Real Application Clusters (1)
- Oracle Reports (1)
- Oracle Security (1)
- Oracle Wallet (1)
- Orasrp (1)
- Organizational Change (1)
- Os (1)
- Osbws_Install.Jar (1)
- Oui Gui (1)
- Output (1)
- Owox (1)
- Paas (1)
- Package Deployment Wizard Error (1)
- Parallel Execution (1)
- Parallel Query (1)
- Parallel Query Downgrade (1)
- Partitioning (1)
- Partitions (1)
- Patches (1)
- Patchmgr (1)
- Pdb Duplication (1)
- Penalty (1)
- Perfomrance (1)
- Performance Schema (1)
- Pg 15 (1)
- Pg_Rewind (1)
- Pga (1)
- Pipeline Debugging (1)
- Pivot (1)
- Planning (1)
- Plsql (1)
- Policy (1)
- Polybase (1)
- Pq (1)
- Preliminar Connection (1)
- Preliminary Connection (1)
- Privatecloud (1)
- Process Mining (1)
- Production (1)
- Productivity (1)
- Programming (1)
- Prompt Engineering (1)
- Provisioned Iops (1)
- Provisiones Iops (1)
- Proxy Monitoring (1)
- Psu (1)
- Public Cloud (1)
- Pubsub (1)
- Purge (1)
- Purge Thread (1)
- Pythian News (1)
- Python Pandas (1)
- Query Performance (1)
- Quicksight (1)
- Quota Limits (1)
- R12 R12.2 Cp Concurrent Processing Abort (1)
- R12.1.3 (1)
- REF! (1)
- Ram Cache (1)
- Rbac (1)
- Rdb (1)
- Rds_File_Util (1)
- Read Free Replication (1)
- Read Latency (1)
- Recruiting (1)
- Redo Size (1)
- Relational Database Management System (1)
- Release (1)
- Release Automation (1)
- Repair (1)
- Replication Compatibility (1)
- Replication Error (1)
- Repmgr (1)
- Repmgrd (1)
- Resiliency Planning (1)
- Resource Manager (1)
- Resources (1)
- Restore (1)
- Restore Point (1)
- Retail (1)
- Rhel (1)
- Risk (1)
- Risk Management (1)
- Rocksrb (1)
- Rollback (1)
- Rolling Patch (1)
- Row0Purge (1)
- Rpm (1)
- Rule "Existing Clustered Or Clustered-Prepared In (1)
- Running Discovery On Remote Machine (1)
- SSRS Administration (1)
- SaaS (1)
- Sar (1)
- Scaling Ir (1)
- Sccm (1)
- Sccm Powershell (1)
- Scripts (1)
- Sdp (1)
- Secrets (1)
- Securing Sql Server (1)
- Security Compliance (1)
- Sed (Stream Editor) (1)
- Self Hosted Ir (1)
- Semaphore (1)
- Seps (1)
- Serverless Computing (1)
- Serverless Framework (1)
- Service Broker (1)
- Service Bus (1)
- Shared Connections (1)
- Shared Storage (1)
- Shellshock (1)
- Signals (1)
- Slave (1)
- Smart Scan (1)
- Snapshot (1)
- Snowday Fall 2021 (1)
- Socat (1)
- Software Development (1)
- Software Engineering (1)
- Solutions Architecture (1)
- Spanner-Backups (1)
- Sphinx (1)
- Spm (1)
- Ssh User Equivalence (1)
- Ssis Denali Error (1)
- Ssis Install Error E Xisting Clustered Or Cluster (1)
- Ssis Package Deployment Error (1)
- Ssisdb Master Key (1)
- Ssisdb Restore Error (1)
- Sso (1)
- Ssrs 2019 (1)
- Sstable2Json (1)
- Sstableloader (1)
- Sstablesimpleunsortedwriter (1)
- Stack Dump (1)
- Standard Edition (1)
- Startup Process (1)
- Statistics (1)
- Statspack (1)
- Statspack Data Mining (1)
- Statspack Erroneously Reporting (1)
- Statspack Issues (1)
- Storage (1)
- Stored Procedure (1)
- Strategies (1)
- Streaming (1)
- Sunos (1)
- Swap (1)
- Swapping (1)
- Switch (1)
- Syft (1)
- Synapse (1)
- Sync Failed There Is Not Enough Space On The Disk (1)
- Sys Schema (1)
- System Function (1)
- Systems Administration (1)
- T-Sql (1)
- Table Optimization (1)
- Tablespace Growth (1)
- Tablespaces (1)
- Tags (1)
- Tar (1)
- Tde (1)
- Team Management (1)
- Tech Debt (1)
- Technology (1)
- Telegraf (1)
- Tempdb Encryption (1)
- Templates (1)
- Temporary Tablespace (1)
- Tenserflow (1)
- Teradata (1)
- There Is Not Enough Space On The Disk (1)
- Thick Data (1)
- Third-Party Data (1)
- Thrift (1)
- Thrift Data (1)
- Tidb (1)
- Time Series (1)
- Time-Drift (1)
- Tkprof (1)
- Tmux (1)
- Tns (1)
- Trace (1)
- Tracefile (1)
- Training (1)
- Transaction Log (1)
- Transactions (1)
- Transformation Navigator (1)
- Transparent Data Encryption (1)
- Trigger (1)
- Triggers On Memory-Optimized Tables Must Use With (1)
- Troubleshooting (1)
- Tungsten (1)
- Tvdxtat (1)
- U-Sql (1)
- UNDO Tablespace (1)
- Upgrade Issues (1)
- Utl_Smtp (1)
- VDI Jump Host (1)
- Validate Structure (1)
- Validate_Credentials (1)
- Value (1)
- Velocity (1)
- Vertex AI (1)
- Vertica (1)
- Vertical Slicing (1)
- Videos (1)
- Virtual Private Cloud (1)
- Virtualization (1)
- Wait_Timeout (1)
- Weblogic Connection Filters (1)
- Webscale Database (1)
- Windows Powershell (1)
- WiredTiger (1)
- With Native_Compilation (1)
- Workshop (1)
- Workspace Security (1)
- Xbstream (1)
- Xml Publisher (1)
- Zabbix (1)
- dbms_Monitor (1)
- sqltrace (1)
- tracing (1)
- vSphere (1)
- xml (1)
- February 2025 (1)
- January 2025 (2)
- December 2024 (1)
- October 2024 (2)
- September 2024 (7)
- August 2024 (4)
- July 2024 (2)
- June 2024 (6)
- May 2024 (3)
- April 2024 (2)
- February 2024 (1)
- January 2024 (11)
- December 2023 (10)
- November 2023 (11)
- October 2023 (10)
- September 2023 (8)
- August 2023 (6)
- July 2023 (2)
- June 2023 (13)
- May 2023 (4)
- April 2023 (6)
- March 2023 (10)
- February 2023 (6)
- January 2023 (5)
- December 2022 (10)
- November 2022 (10)
- October 2022 (10)
- September 2022 (13)
- August 2022 (16)
- July 2022 (12)
- June 2022 (13)
- May 2022 (11)
- April 2022 (4)
- March 2022 (5)
- February 2022 (4)
- January 2022 (14)
- December 2021 (16)
- November 2021 (11)
- October 2021 (6)
- September 2021 (11)
- August 2021 (6)
- July 2021 (9)
- June 2021 (4)
- May 2021 (8)
- April 2021 (16)
- March 2021 (16)
- February 2021 (6)
- January 2021 (12)
- December 2020 (12)
- November 2020 (17)
- October 2020 (11)
- September 2020 (10)
- August 2020 (11)
- July 2020 (13)
- June 2020 (6)
- May 2020 (9)
- April 2020 (18)
- March 2020 (21)
- February 2020 (13)
- January 2020 (15)
- December 2019 (10)
- November 2019 (11)
- October 2019 (12)
- September 2019 (16)
- August 2019 (15)
- July 2019 (10)
- June 2019 (16)
- May 2019 (20)
- April 2019 (21)
- March 2019 (14)
- February 2019 (18)
- January 2019 (18)
- December 2018 (5)
- November 2018 (16)
- October 2018 (12)
- September 2018 (20)
- August 2018 (27)
- July 2018 (31)
- June 2018 (34)
- May 2018 (28)
- April 2018 (27)
- March 2018 (17)
- February 2018 (8)
- January 2018 (20)
- December 2017 (14)
- November 2017 (4)
- October 2017 (1)
- September 2017 (3)
- August 2017 (5)
- July 2017 (4)
- June 2017 (2)
- May 2017 (7)
- April 2017 (7)
- March 2017 (8)
- February 2017 (8)
- January 2017 (5)
- December 2016 (3)
- November 2016 (4)
- October 2016 (8)
- September 2016 (9)
- August 2016 (10)
- July 2016 (9)
- June 2016 (8)
- May 2016 (13)
- April 2016 (16)
- March 2016 (13)
- February 2016 (11)
- January 2016 (6)
- December 2015 (11)
- November 2015 (11)
- October 2015 (5)
- September 2015 (16)
- August 2015 (4)
- July 2015 (1)
- June 2015 (3)
- May 2015 (6)
- April 2015 (5)
- March 2015 (5)
- February 2015 (4)
- January 2015 (3)
- December 2014 (7)
- October 2014 (4)
- September 2014 (6)
- August 2014 (6)
- July 2014 (16)
- June 2014 (7)
- May 2014 (6)
- April 2014 (5)
- March 2014 (4)
- February 2014 (10)
- January 2014 (6)
- December 2013 (8)
- November 2013 (12)
- October 2013 (9)
- September 2013 (6)
- August 2013 (7)
- July 2013 (9)
- June 2013 (7)
- May 2013 (7)
- April 2013 (4)
- March 2013 (7)
- February 2013 (4)
- January 2013 (4)
- December 2012 (6)
- November 2012 (8)
- October 2012 (9)
- September 2012 (3)
- August 2012 (5)
- July 2012 (5)
- June 2012 (7)
- May 2012 (11)
- April 2012 (1)
- March 2012 (8)
- February 2012 (1)
- January 2012 (6)
- December 2011 (8)
- November 2011 (5)
- October 2011 (9)
- September 2011 (6)
- August 2011 (4)
- July 2011 (1)
- June 2011 (1)
- May 2011 (5)
- April 2011 (2)
- February 2011 (2)
- January 2011 (2)
- December 2010 (1)
- November 2010 (7)
- October 2010 (3)
- September 2010 (8)
- August 2010 (2)
- July 2010 (4)
- June 2010 (7)
- May 2010 (2)
- April 2010 (1)
- March 2010 (3)
- February 2010 (3)
- January 2010 (2)
- November 2009 (6)
- October 2009 (6)
- August 2009 (3)
- July 2009 (3)
- June 2009 (3)
- May 2009 (2)
- April 2009 (8)
- March 2009 (6)
- February 2009 (4)
- January 2009 (3)
- November 2008 (3)
- October 2008 (7)
- September 2008 (6)
- August 2008 (9)
- July 2008 (9)
- June 2008 (9)
- May 2008 (9)
- April 2008 (8)
- March 2008 (4)
- February 2008 (3)
- January 2008 (3)
- December 2007 (2)
- November 2007 (7)
- October 2007 (1)
- August 2007 (4)
- July 2007 (3)
- June 2007 (8)
- May 2007 (4)
- April 2007 (2)
- March 2007 (2)
- February 2007 (5)
- January 2007 (8)
- December 2006 (1)
- November 2006 (3)
- October 2006 (4)
- September 2006 (3)
- July 2006 (1)
- May 2006 (2)
- April 2006 (1)
- July 2005 (1)
No Comments Yet
Let us know what you think