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Dariusz Owczarek

Oracle GoldenGate Best Practices and Tips - 0 views

  • PARALLEL PROCESSING Ensure the system has enough shared memory. GoldenGate runs as an Oracle process. Each Extract or Replicat process requires upwards of 25-50 MB of system shared memory. This means less memory for the Oracle DBMS, especially the SGA. Use parallel Replicat groups on the target system to reduce latency thru parallelism. Consider parallel Extract groups for tables that are fetch intensive (e.g., those that trigger SQL procedures). Group tables that have R.I. to each other in the same Extract-Replicat pair. Pair each Replicat with its own trail and corresponding Extract process. When using parallel Replicats, configure each one to process a different portion of the overall data.
  • PASSTHRU PARAMETER Consider using this parameter if there is no filtering, conversion or mapping required and you’re using DATAPUMP. In pass-through mode, the Extract process does not look up table definitions, either from the database or from a data definitions file. Pass-through mode increases the throughput of the data pump, because all of the functionality that looks up object definitions is bypassed. This saves database fetches to improve performance.
  • INSERTAPPEND A new GoldenGate 10.4 feature. Use for large transactions . Puts records at end of table rather than doing a more costly insert into other areas of table.
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  • To reduce bandwidth requirements: Use compression options of the RMTHOST parameter to compress data before it is sent across the network. Weigh the benefits of compression against the CPU resources that are required to perform the compression.
  • To increase the TCP/IP packet size: Use the TCPBUFSIZE option of the RMTHOST parameter to increase the size of the TCP socket buffer that Extract maintains. By increasing the size of the buffer, you can send larger packets to the target system. Consult with Network Support before setting TCPBUFSIZE.
  • Use SQL Arrays The BATCHSQL parameter will increase the performance of Replicat. BATCHSQL causes Replicat to create arrays for similar SQL statements and apply them at an accelerated rate. Normally, Replicat applies one SQL statement at a time.
  • Use the CHECKPOINTSECS in Extract or Replicat; if increased, less frequent checkpoints; increases data to be reprocessed if process fails; keep transaction logs available in case of reprocessing
  • Use the GROUPTRANSOPS; increases number of SQL operations in a Replicat ; reduces I/O to checkpoint file and checkpoint table.
  • Data Filtering and Conversion: Use primary Extract for data capture only. Use a data pump on the source to perform filtering and thereby send less data over the network. Alternatively, use Replicat for conversion and, if the network can handle large amounts of data, also for filtering.
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    Oracle GoldenGate Best Practices and Tips
donaldjmarshal

Zero Cost Cloud Migration Services | Migration Of Workloads to Cloud | Suneratech - 0 views

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    Zero Cost Cloud Migration CLOUD-FIRST is a captivating concept around which the emerging businesses are predominantly dependent upon. While it aligns with the digital transformation strategies built for enterprises, migrating workloads to cloud comes with its own challenges like flexibility, application performance and budgets. more details visit Zero cost cloud Migration services In a data-driven world, you need a comprehensive business model to accelerate your IT transformation with cloud services and offering you the advantages of a cloud. Suneratech improves your business agility, security, cost-efficiency, and simplicity, with a 4-step strategy to move you to cloud while reaping the benefits. ZCCM Advantage for Customers When a customer withdraws from other service providers like IBM or OMCS, and opt for a new provider, a customer must pay for both the providers until the migration is completed. ZCCM program is a great choice for such customers, as it saves this double cost by paying all the Oracle costs until the customer's contract terminates with other cloud service providers. Suneratech migrates all workloads in scope to Oracle Cloud Infrastructure (OCI), at ZERO Cost, and will not invoice until all workloads are successfully migrated to Cloud.
Dariusz Owczarek

RAC Hot Block Issue - 0 views

  • One obvious method of reducing pings between instances is to isolate the transactions that use a specific data set to a specific server in the RAC cluster.
  • Some of the good RAC practices, to put it quite frankly, waste disk and memory space to improve data sharing and dispersal characteristics.
  • An example of an efficient RAC object is one that is used by only a single instance at a time. To achieve this singularity of use, the rows-per-block (RPB) of the data object must be reduced.
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  • For high insert objects, pre-allocate extents to avoid dynamic space management. Assign allocated extents to specific instances. This avoids intra-instance block transfers during insert activity from multiple nodes.
  • Use reverse-key indexes for indexes that may become right-hand indexes due to high insert rates. This removes the capability to use index scans. Use only when required.
  • Design indexes such that the clustering factor is as close to the number of used blocks as is possible.
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    Compartmenting Transactions to Specific Nodes - rows per block (RPB)
Dariusz Owczarek

Oracle Diagnostic Tools - 0 views

  • Enterprise Manager A graphical all-purpose tool that can be used to identify when a spike occurred, drill down to the cause, and examine ADDM recommendations. The benefit of a graphical representation of performance data is visible (pun intended). Data visualizations display any skew directly.
  • Automatic Database Diagnostic Monitor (ADDM) An expert system that automatically identifies and recommends solutions for many instance-wide performance problems. Best used for longer-duration performance problems (that is, problems that are continuous or ongoing for a large proportion of the snapshot interval). The symptoms and problems are available by running the ADDM report, and through Enterprise Manager.
  • Active Session History (ASH) An all-purpose tool providing data that is useful when investigating system-wide problems, shorter-duration spikes, or smaller-scoped problems (for example, for a specific user, or SQL, or a module/action).The advantage of using ASH data when compared to other diagnostic information is that the data is of a finer granularity. This allows you to look at a problem to identify how the symptoms "build up," or allows you to determine exactly which resources are involved and who is using them. The ASH data can be queried directly or accessed via a targeted ASH report.
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  • Automatic Workload Repository (AWR) Instance-wide summary data that is used when ADDM is not able to identify the problem in the system, and the problem is of longer duration. Also used to verify the ADDM analysis. The data can be queried directly but is most often accessed via the AWR instance report.
  • Statspack (SP) Instance-wide summary data used to manually diagnose performance problems. You should use SP when you are not licensed for the Diagnostics Pack, and so can't use ADDM or AWR.
  • SQL trace This traces the execution flow (resource utilization, execution plan, and waits) by SQL statement. The information can be used to examine the flow and resource utilization for a specific user, feature, or SQL statement identified as problematic.
Dariusz Owczarek

Meaning of Oracle Key Statistics - 0 views

  • Statistics are somewhat fallible in that they are seldom 100 percent accurate, but in most cases they do sufficiently indicate what was intended. Be sure you understand what each statistic represents and the units used (there is a big difference between microseconds and centiseconds).
  • Time-breakdown statistics (Time Model) make it significantly easier to determine the type of operations that are consuming resources in the database.
  • DB time: Time spent by all user processes in the database (that is,. non-idle wait time + CPU time).
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  • DB CPU: Time spent by all user processes on the CPU, in Oracle code. On most systems, the majority of time will be spent in DB CPU, SQL execute elapsed time, or PL/SQL execution elapsed time (and possibly Java). Time spent in parse and connection management should be low, so if the levels indicate a high percentage of DB time, a problem exists in the relevant area. You can use this data to correlate with Top 5 Timed Events and Load Profile.
  • Database time (DB time) is an important time-based statistic: it measures the total time spent in the database by active sessions (that is, foreground user processes either actively working or actively waiting in a database call). DB time includes CPU time, I/O time, and other non-idle wait time.
  • Because DB time represents the sum of the time that all sessions spend in database calls, it can easily exceed the elapsed wall-clock time.
  • The objective of tuning an Oracle system could be stated as reducing the time that users spend in performing actions in the database, or simply reducing DB time.
  • Wait time is artificially inflated when the host is CPU bound because the wait time includes the actual time spent waiting (for example, waiting for a disk I/O), as well as the time spent by the process in the OS run-queue waiting to be rescheduled.
  • Therefore, when the host is CPU bound, it is important to reduce CPU utilization before addressing wait-related problems, because otherwise you may be addressing the wrong problem.
  • You can use ASH data to estimate DB time when the actual DB time is not available—for example, if a session has exited. Because ASH samples active sessions every second, you can estimate DB time (in seconds) to be the number of ASH samples counted.
  • V$OSSTAT is OS-related resource utilization data that the Oracle server collects. The statistics available vary by platform. You can use V$OSSTAT to determine CPU utilization (BUSY_TICKS and IDLE_TICKS), and also compare this to the host's CPU utilization statistics. Also look for high OS_CPU_WAIT_TIME, which may indicate the host is CPU bound.
  • V$OSSTAT statistics can be compared with the Time Model statistics, for example to determine how much of the total CPU used on the host is attributable to this instance: DB CPU / BUSY_TICKS.
  • note that the units for these two statistics differ.
  • In 10g, each wait event (V$SYSTEM_EVENT) is classified into one of nine wait classes: Application, Commit, Concurrency, Configuration, Network, Other, System I/O, User I/O, and Idle. The class names are reasonably self-explanatory except Other, which is a catchall bucket for wait events that should not ever contribute any significant wait time.
Dariusz Owczarek

Hash partitioning - 0 views

  • - instead of having a 100 gig tablespace to backup, you have 100, 1 gig tablespaces. (each tablespace spends less time in backup mode, reduces the amount of potential extra redo, reduces the amount of manual recovery you need to do if the instance failes during backup). same with restores.
  • every single admin option you do to a partition applies to a hash partition
  • Say you do a join on the hash partition key -- we can do parallel partition wise elimination on the join
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  • Hash partitioning -- all of admin features of range partitions and many of the partition elimination/query features as well.
  • With a harsh partition, we are attempting to achieve an EVEN distribution of data across all of the partitions while at the same time supporting partition elimination and other features.
  • you want an ALMOST unique or unique value to hash on
  • with hashing -- all rows with the same key by definition hash to the same partition -- that is the very essence of hash partitioning
  • you would just drop/truncate the oldest partition and if you do this with the option to maintain the indexes, it'll not impose any sort of rebuild
  • with hash partitions, you want to hash on something that is almost unique (or at least has lots of values) and into powers of 2 you want 2, 4, 8, 16, 32, 64, 128, .... partitions. 50 is not going to work (you'll always get a bell shape with the partitions at the front and end having the least and the ones in the middle having the most)
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    Hash partitioning
Dariusz Owczarek

Configuration of TAF (Transparent Application Failover) and Load Balancing - 0 views

  • The client load balancing feature enables clients to randomize connection requests among the listeners. Tnsnames Parameter: LOAD_BALANCE
  • The connect-time failover enables clients to connect to another listener if the initial connection to the first listener fails. The number of listener protocol addresses determines how many listeners are tried. Without connect-time failover, Oracle Net attempts a connection with only one listener. The default is on. Tnsnames Parameter: FAILOVER
  • The listener connection load balancing feature improves connection performance by balancing the number of active connections among multiple dispatchers and instances. In a single-instance environment, the listener selects the least loaded dispatcher to handle the incoming client requests. In an Oracle Real Application Clusters (RAC) environment, connection load balancing also has the capability to balance the number of active connections among multiple instances. 1. Least-loaded node 2. Least-loaded instance 3. Least-loaded dispatcher for that instance (in case of Shared server configuration)
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  • Transparent Application Failover (TAF) is a feature of the Oracle Call Interface (OCI) driver at client side. It enables the application to automatically reconnect to a database, if the database instance to which the connection is made fails. In this case, the active transactions roll back. Tnsnames Parameter: FAILOVER_MODE
  • Doc ID: 453293.1
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    This note explains the configuration in 10g & 11g for: Client Side Connect Time Load Balance; Client Side Connect Time Failover; Server Side Listener; Connection Load Balance; Transparent Application Failover (TAF)
Dariusz Owczarek

Can not start Webcache component of OMS - 0 views

  • failed to start a managed process after the maximum retry limit Log: /home/oracle/product/10.2.0/oms10g/opmn/logs/WebCache~WebCache~1
  • failed to start a managed process after the maximum retry limit Log: /home/oracle/product/10.2.0/oms10g/opmn/logs/WebCache~WebCacheAdmin~1
  • b.Login as root user and execute following command OMS_HOME/webcache/bin/webcache_setuser.sh setroot <username> Note: In place of the <username> you should give the user name which you use to start oms.
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    Can not start WebCache component of OMS. opmnctl returns "failed to start a managed process after the maximum retry limit". Applies to Enterprise Manager Grid Control - Version: 10.2.0.1 to 10.2.0.5, can occur on any platform.
paul silmonet

Instant Fix Slow Computer Solutions - 0 views

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sqwor3

Seeking Sage Advice on LMS MVP Creation - 2 views

You're wise to consider an MVP approach for your LMS startup idea after seeing your friend's painful failure going all-in without validation. Those kinds of cautionary tales reinforce why the lean ...

Dariusz Owczarek

SQL GRANT Syntax - 0 views

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    SQL GRANT statement is used to grant system or object privileges to users and roles. It is also used to grant roles to users and roles.
samantha armstrong

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Dariusz Owczarek

How To Configure Dispatchers For RAC Environment - 0 views

  • Doc ID: 578524.1
  • Note: It is very important to use entire address string in order to configure dispatchers on RAC and host name used in it should be a VIP hostname, otherwise connection may suffer intermittent ORA-12545 errors. Refer metalink note <333159.1>
  • alter system set dispatchers='(address=(protocol=tcp)(host=node1-vip))(dispatchers=2)' scope=both   sid='racdb1';
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  • If you have a firewall present between client and the server, then it may block connections on the randomly selected dispatchers ports. If this is the case for your setup then set the dispatcher with PORT clause as below and configure the firewall to allow the communication on these ports along with the listener port.
  • alter system set dispatchers='(address=(protocol=tcp)(host=<vip address>)(port=<port_number>))' scope=both sid='racdb1';
  • Note - If the port clause is not used in the dispatchers configuration then port numbers will be chosen randomly which could be blocked in the firewall resulting redirected connection to dispatchers getting time out errors. For more details refer note <125021.1>:Oracle Connections and Firewalls
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    This document would guide you to configure dispatchers for Real Application Cluster (RAC) database.
Dariusz Owczarek

A UML Profile for Data Modeling - 0 views

  • Unfortunately data modeling is not yet covered by the Unified Modeling Language (UML), even though persistence-related issues are clearly an important aspect of object-oriented software project.
  • The good news is that the Object Management Group (OMG) issued an RFP for an official UML Data Modeling Profile in December 2005.
  • This page summarizes the data modeling profile for UML Class Diagrams, that I apply in Agile Database Techniques, The Object Primer 3rd Edition, and Refactoring Databases.  First some important definitions:
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  • Logical data models (LDMs).  LDMs are used to explore either the conceptual design of a database or the detailed data architecture of your enterprise.  LDMs depict the logical data entities, typically referred to simply as data entities, the data attributes describing those entities, and the relationships between the entities.
  • Physical data models (PDMs).  PDMs are used to design the internal schema of a database, depicting the data tables, the data columns of those tables, and the relationships between the tables.
  • Conceptual data models.  These models are typically used to explore domain concepts with project stakeholders.  Conceptual data models are often created as the precursor to LDMs or as alternatives to LDMs.
Dariusz Owczarek

Oracle ASSM Performance - 0 views

  • Cons of ASSM: §         Slow for full-table scans: Several studies have shown that large-table full-table scans (FTS) will run longer with ASSM than standard bitmaps. ASSM FTS tablespaces are consistently slower than freelist FTS operations. This implies that ASSM may not be appropriate for decision support systems and warehouse applications unless partitioning is used with Oracle Parallel Query. §        Slower for high-volume concurrent inserts: Numerous experts have conducted studies that show that tables with high volume bulk loads perform faster with traditional multiple freelists. §         ASSM will influence index clustering: For row ordered tables, ASSM can adversely affect the clustering_factor for indexes. Bitmap freelists are less likely to place adjacent tows on physically adjacent data blocks, and this can lower the clustering_factor and the cost-based optimizer's propensity to favor an index range scan.
  • Pros of ASSM: §          Varying row sizes: ASSM is better than a static pctused. The bitmaps make ASSM tablespaces better at handling rows with wide variations in row length. §         Reducing buffer busy waits: ASSM will remove buffer busy waits better than using multiple freelists. When a table has multiple freelists, all purges must be parallelized to reload the freelists evenly, and ASSM has no such limitation. §         Great for Real Application Clusters: The bitmap freelists remove the need to define multiple freelists groups for RAC and provide overall improved freelist management over traditional freelists.
  • Cons of ASSM: §         Slow for full-table scans: Several studies have shown that large-table full-table scans (FTS) will run longer with ASSM than standard bitmaps. ASSM FTS tablespaces are consistently slower than freelist FTS operations. This implies that ASSM may not be appropriate for decision support systems and warehouse applications unless partitioning is used with Oracle Parallel Query. §          Slower for high-volume concurrent inserts: Numerous experts have conducted studies that show that tables with high volume bulk loads perform faster with traditional multiple freelists. §          ASSM will influence index clustering: For row ordered tables, ASSM can adversely affect the clustering_factor for indexes. Bitmap freelists are less likely to place adjacent tows on physically adjacent data blocks, and this can lower the clustering_factor and the cost-based optimizer's propensity to favor an index range scan.
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    Oracle ASSM Performance pros and cons
Dariusz Owczarek

Oracle's V$ Views - Dynamic Performance Views - 1 views

  • v$database This view lets you access database information.
  • v$datafile This view contains an entry for each datafile of the database.
  • v$dataguard_status Shows error messages in a data guard environment.
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  • v$flash_recovery_area_usage See also v$recovery_file_dest
  • v$lock This view stores all information relating to locks in the database.
  • v$mystat This view records statistical data about the session that accesses it.
  • v$parameter Lists the name-value pairs of the init.ora file (or their default, if not in the init.ora).
  • v$session
  • v$session_longops Use v$session_longops if you have a long running pl/sql procedure and want to give feedback on how far the procedure proceeded.
  • v$session_wait This views shows what wait event each session is waiting for, or what the last event was that it waited for.
  • v$session_wait_history This view is new in Oracle 10g and allows improved timing and statistics.
  • v$sqlarea Join v$sqlarea's address with v$session's sql_address.
  • v$sql_bind_capture New with Oracle 10g This view captures bind variables for all sessions and is faster than setting 10046 on level 4.
  • v$version Use this view to find out what version you actually work on: select * from v$version;
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    Oracle's data dictionary provides information that Oracle needs to perform its tasks. The data dictionary is stored in table structures owned by SYS. Their content is exposed through dictionary views. Dynamic performance views (so called v$ views) are part of Oracle's data dictionary.
Dariusz Owczarek

Oracle announces availability of Oracle Database 11g Release 2 - 0 views

  • In this release, Edition-based Redefinition is introduced to allow customer database applications to be upgraded online; this removes the need for separate upgrade environments.
  • This release also delivers enhanced query performance with the ability to transparently execute a query against data stored in memory across all the servers in a grid.
  • In this release, Oracle Automatic Storage Management is extended to support a general-purpose cluster file system to help customers reduce their storage management costs.
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  • The combination of Oracle Database 11g Release 2 Advanced Compression and Partitioning support the reduction of storage costs by compressing data as much as 2-4x and simplifying use of lower cost storage tiers.
Dariusz Owczarek

Adaptive Cursor Sharing - 0 views

  • Adaptive Cursor Sharing is a new feature starting from Oracle version 11g release 1. The idea behind is to improve the execution plans for statements with bind variables. CBO has been enhanced to allow multiple execution plans to be used for a single statement with bind variables, without hard parsing the SQL.
  • There is no special way to configure ACS. It is on by default and of course there is a hidden initialization parameter to turn it off if needed. Key role in the process of decision whether ACS will be used for a particular statement are: Two new columns in V$SQL view (IS_BIND_SENSITIVE and IS_BIND_AWARE) Three new views (V$SQL_CS_HISTOGRAM, V$SQL_CS_SELECTIVITY, V$SQL_CS_STATISTICS)
donaldjmarshal

Cloud Migration Services | Migrating Workloads to Cloud | Suneratech - 0 views

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    Migrations pose tough challenges that can be met only with a careful strategy and the right resources at hand. Cloud migrations pave the way for DevOps, Automation, better Data Integration and, ultimately, Digital Transformation However, moving to the cloud adds tangible business value and reduces the risk & challenge of change. Suneratech helps you execute your cloud migration strategy with a strategic approach that includes data center, apps, infrastructure, security, and OMCS. As a Cloud migration partner for our varied clientele, Suneratech has successfully migrated over 700 workloads to the cloud.
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