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  • Oracle query nnnnnnnnnnnn

    - by kunj raman singh
    Hi, Please help me to achieve the below problem: I am having one "view" in the Oracle database,I want the output of that view and store that output in the .txt file on some other folder in UNIX box. The output which is generated from view is a report and I want to save that report in .txt format in one folder on UNIX box.Oracle is present on the UNIX box.

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  • When would isSearchable return false for an Oracle JDBC column?

    - by Ian Varley
    In what cases would a call to java.sql.ResultSetMetaData.isSearchable(int col) return false for an Oracle database? The documentation for the method doesn't really answer the question: "Indicates whether the designated column can be used in a where clause." I can think of only one case - when the column is the result of an aggregate function (in which case it would have to be part of a HAVING filter, not a WHERE filter). Are there any other cases?

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  • oracle index for string column - does format of data affects quality of index?

    - by Jayan
    We have following type of "Unique ID" column for many tables in the database (Oracle). It is a string with following format <randomnumber>-<ascendingnumber>-<machinename> So we have some thing like this U1234-12345-NBBJD U1234-12346-NBBJD U1234-12347-NBBJD U1234-12348-NBBJD U1234-12349-NBBJD The UID value is unique, we have unique index on them. Does the following format is more efficient than above for index scans? NBBJD-U1234-12345 NBBJD-U1234-12346 NBBJD-U1234-12347 NBBJD-U1234-12348 NBBJD-U1234-12349

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  • Actual SQL statement after bind variables specified

    - by bioffe
    I am trying to log every SQL statement executed from my scripts. However I contemplate one problem I can not overcome. Is there a way to compute actual SQL statement after bind variables were specified. In SQLite I had to compute the statement to be executed manually, using code below: def __sql_to_str__(self, value,args): for p in args: if type(p) is IntType or p is None: value = value.replace("?", str(p) ,1) else: value = value.replace("?",'\'' + p + '\'',1) return value It seems CX_Oracle has cursor.parse() facilities. But I can't figure out how to trick CX_Oracle to compute my query before its execution.

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  • apex button to call a page in another application

    - by jaykio77
    I have a workspace with which I have 5 applications based on same schema. Now I want to have a main page from where I could call main pages of all these applications. I used this syntax to call home page in another application but to no avail f?p=4000:4150:&APP_SESSION. Where 4000:4150 are the values for the application and the page I want to display. Please let me know where am I making mistake.

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  • Oracle: how to UPSERT (update or insert into a table?)

    - by Mark Harrison
    The UPSERT operation either updates or inserts a row in a table, depending if the table already has a row that matches the data: if table t has a row exists that has key X: update t set mystuff... where mykey=X else insert into t mystuff... Since Oracle doesn't have a specific UPSERT statement, what's the best way to do this?

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  • Oracle: How can I know a table is getting populated?

    - by Tami
    Hi, I'm in charge of an oracle db where we don't have any documentation (at all). And at the moment I need to know HOW a table is getting populated. Ideally, I'd like to know from which procedure, trigger, whatever... this table gets its data from. Any idea would be much appreciated. Thanks.

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  • move data in bulk from oracle to SQL database

    - by Soja
    Hi All... Would like to know which is the best way to move data in bulk from oracle to SQL database programmatically in VB.NET application.This application is suppose to run continuously and moves data from Oracle to SQL whenever data comes. I have found OPENDATASOURCE but does not know the exact syntax. Can someone help me out. Thanks in advance,

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  • Can PHP and Oracle pass complex types to each other?

    - by RenderIn
    I want to pass/bind an array of (key1, key2) to an Oracle PL/SQL stored procedure using PHP. I'm able to bind primitive types and arrays of primitive types, but haven't found a way to pass complex datatypes back and forth. Is this unsupported? So far I've been having to pass along multiple arrays -- one for each subtype in my complex type -- and then depend on their indexes to reconstitute them in the procedure.

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  • EPM Infrastructure Tuning Guide v11.1.2.2 / 11.1.2.3

    - by Ahmed Awan
    Applies To: This edition applies to only 11.1.2.2, 11.1.2.3. One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle EPM System performance, all components need to be monitored, analyzed, and tuned. This guide describe the techniques used to monitor performance and the techniques for optimizing the performance of EPM components. TOP TUNING RECOMMENDATIONS FOR EPM SYSTEM: Performance tuning Oracle Hyperion EPM system is a complex and iterative process. To get you started, we have created a list of recommendations to help you optimize your Oracle Hyperion EPM system performance. This chapter includes the following sections that provide a quick start for performance tuning Oracle EPM products. Note these performance tuning techniques are applicable to nearly all Oracle EPM products such as Financial PM Applications, Essbase, Reporting and Foundation services. 1. Tune Operating Systems parameters. 2. Tune Oracle WebLogic Server (WLS) parameters. 3. Tune 64bit Java Virtual Machines (JVM). 4. Tune 32bit Java Virtual Machines (JVM). 5. Tune HTTP Server parameters. 6. Tune HTTP Server Compression / Caching. 7. Tune Oracle Database Parameters. 8. Tune Reporting And Analysis Framework (RAF) Services. 9. Tune Oracle ADF parameters. Click to Download the EPM 11.1.2.3 Infrastructure Tuning Whitepaper (Right click or option-click the link and choose "Save As..." to download this pdf file)

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  • MySQL Connect: What to Expect From the Wondrous Land of MySQL Cluster

    - by Mat Keep
    The MySQL Connect conference is only a couple of weeks away, with MySQL engineers, support teams, consultants and community aces busy putting the final touches to their talks. There will be many exciting new announcements and sharing of best practices at the conference, covering the range of MySQL technologies. MySQL Cluster will a big part of this, so I wanted to share some key sessions for those of you who plan on attending, as well as some resources for those who are not lucky enough to be able to make the trip, but who can't afford to miss the key news. Of course, this is no substitute to actually being there….and the good news is that registration is still open ;-) Roadmap: Whats New in MySQL Cluster Saturday 29th, 1300-1400, in Golden Gate room 5.                                                                                        Bernd Ocklin, director of MySQL Cluster development, and myself will be taking a look at what follows the latest MySQL Cluster 7.2 release. I don't want to give to much away - lets just say its not often you can add powerful new functionality to a product while at the same time making life radically simpler for its users. For those not making it to the Conference, a live webinar repeating the talk is scheduled for Thursday 25th October at 09.00 pacific time. Hold the date, registration will be open for that soon and published to our MySQL Webinars page Best Practices Getting Started with MySQL Cluster, Hands-On Lab Saturday 29th, 1600-1700, in Plaza Room A.                                                              Santo Leto, one of our lead MySQL Cluster support engineers, regularly works with users new to MySQL Cluster, assisting them in installation, configuration, scaling, etc. In this lab, Santo will share best-practices in getting started. Delivering Breakthrough Performance with MySQL Cluster Saturday 29th, 1730-1830, in Golden Gate room 5. Frazer Clement, lead MySQL Cluster software engineer, will demonstrate how to translate the awesome Cluster benchmarks (remember 1 BILLION UPDATEs per minute ?!) into real-world performance. You can also get some best practices from our new MySQL Cluster performance guide  MySQL Cluster BoF Saturday 29th, 1900-2000, room Golden Gate 5.                                                                                                           Come and get a demonstration of new tools for the installation and configuration of MySQL Cluster, and spend time with the engineering team discussing any questions or issues you may have. Developing High-Throughput Services with NoSQL APIs to InnoDB and MySQL Cluster Sunday 30th, 1145 - 1245, in Golden Gate room 7.   In this session, JD Duncan and Andrew Morgan will present how to get started with both Memcached and new NoSQL APIs. JD and I recently ran a webinar demonstrating how to build simple Twitter-like services with Memcached and MySQL Cluster. The replay is available for download.  Case Studies: MySQL Cluster @ El Chavo, Latin America’s #1 Facebook Game Sunday 30th, 1745 - 1845, in Golden Gate room 4.                             Playful Play deployed MySQL Cluster CGE to power their market leading social game. This session will discuss the challenges they faced, why they selected MySQL Cluster and their experiences to date. You can read more about Playful Play and MySQL Cluster here  A Journey into NoSQLand: MySQL’s NoSQL Implementation Sunday 30th, 1345 - 1445, in Golden Gate room 4.                                          Lig Turmelle, web DBA at Kaplan Professional and esteemed Oracle Ace, will discuss her experiences working with the NoSQL interfaces for both MySQL Cluster and InnoDB Evaluating MySQL HA Alternatives Saturday 29th, 1430-1530, room Golden Gate 5                                                                                   Henrik Ingo, former member of the MySQL sales engineering team, will provide an overview of various HA technologies for MySQL, starting with replication, progressing to InnoDB, Galera and MySQL Cluster What about the other stuff? Of course MySQL Connect has much, much more than MySQL Cluster. There will be lots on replication (which I'll blog about soon), MySQL 5.6, InnoDB, cloud, etc, etc. Take a look at the full Content Catalog to see more. If you are attending, I hope to see you at one of the Cluster sessions...and remember, registration is still open

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  • Understanding G1 GC Logs

    - by poonam
    The purpose of this post is to explain the meaning of GC logs generated with some tracing and diagnostic options for G1 GC. We will take a look at the output generated with PrintGCDetails which is a product flag and provides the most detailed level of information. Along with that, we will also look at the output of two diagnostic flags that get enabled with -XX:+UnlockDiagnosticVMOptions option - G1PrintRegionLivenessInfo that prints the occupancy and the amount of space used by live objects in each region at the end of the marking cycle and G1PrintHeapRegions that provides detailed information on the heap regions being allocated and reclaimed. We will be looking at the logs generated with JDK 1.7.0_04 using these options. Option -XX:+PrintGCDetails Here's a sample log of G1 collection generated with PrintGCDetails. 0.522: [GC pause (young), 0.15877971 secs] [Parallel Time: 157.1 ms] [GC Worker Start (ms): 522.1 522.2 522.2 522.2 Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] [Processed Buffers : 2 2 3 2 Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] [GC Worker Other (ms): 0.3 0.3 0.3 0.3 Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] [Clear CT: 0.1 ms] [Other: 1.5 ms] [Choose CSet: 0.0 ms] [Ref Proc: 0.3 ms] [Ref Enq: 0.0 ms] [Free CSet: 0.3 ms] [Eden: 12M(12M)->0B(10M) Survivors: 0B->2048K Heap: 13M(64M)->9739K(64M)] [Times: user=0.59 sys=0.02, real=0.16 secs] This is the typical log of an Evacuation Pause (G1 collection) in which live objects are copied from one set of regions (young OR young+old) to another set. It is a stop-the-world activity and all the application threads are stopped at a safepoint during this time. This pause is made up of several sub-tasks indicated by the indentation in the log entries. Here's is the top most line that gets printed for the Evacuation Pause. 0.522: [GC pause (young), 0.15877971 secs] This is the highest level information telling us that it is an Evacuation Pause that started at 0.522 secs from the start of the process, in which all the regions being evacuated are Young i.e. Eden and Survivor regions. This collection took 0.15877971 secs to finish. Evacuation Pauses can be mixed as well. In which case the set of regions selected include all of the young regions as well as some old regions. 1.730: [GC pause (mixed), 0.32714353 secs] Let's take a look at all the sub-tasks performed in this Evacuation Pause. [Parallel Time: 157.1 ms] Parallel Time is the total elapsed time spent by all the parallel GC worker threads. The following lines correspond to the parallel tasks performed by these worker threads in this total parallel time, which in this case is 157.1 ms. [GC Worker Start (ms): 522.1 522.2 522.2 522.2Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] The first line tells us the start time of each of the worker thread in milliseconds. The start times are ordered with respect to the worker thread ids – thread 0 started at 522.1ms and thread 1 started at 522.2ms from the start of the process. The second line tells the Avg, Min, Max and Diff of the start times of all of the worker threads. [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] This gives us the time spent by each worker thread scanning the roots (globals, registers, thread stacks and VM data structures). Here, thread 0 took 1.6ms to perform the root scanning task and thread 1 took 1.5 ms. The second line clearly shows the Avg, Min, Max and Diff of the times spent by all the worker threads. [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] Update RS gives us the time each thread spent in updating the Remembered Sets. Remembered Sets are the data structures that keep track of the references that point into a heap region. Mutator threads keep changing the object graph and thus the references that point into a particular region. We keep track of these changes in buffers called Update Buffers. The Update RS sub-task processes the update buffers that were not able to be processed concurrently, and updates the corresponding remembered sets of all regions. [Processed Buffers : 2 2 3 2Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] This tells us the number of Update Buffers (mentioned above) processed by each worker thread. [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] These are the times each worker thread had spent in scanning the Remembered Sets. Remembered Set of a region contains cards that correspond to the references pointing into that region. This phase scans those cards looking for the references pointing into all the regions of the collection set. [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] These are the times spent by each worker thread copying live objects from the regions in the Collection Set to the other regions. [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] Termination time is the time spent by the worker thread offering to terminate. But before terminating, it checks the work queues of other threads and if there are still object references in other work queues, it tries to steal object references, and if it succeeds in stealing a reference, it processes that and offers to terminate again. [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] This gives the number of times each thread has offered to terminate. [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] These are the times in milliseconds at which each worker thread stopped. [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] These are the total lifetimes of each worker thread. [GC Worker Other (ms): 0.3 0.3 0.3 0.3Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] These are the times that each worker thread spent in performing some other tasks that we have not accounted above for the total Parallel Time. [Clear CT: 0.1 ms] This is the time spent in clearing the Card Table. This task is performed in serial mode. [Other: 1.5 ms] Time spent in the some other tasks listed below. The following sub-tasks (which individually may be parallelized) are performed serially. [Choose CSet: 0.0 ms] Time spent in selecting the regions for the Collection Set. [Ref Proc: 0.3 ms] Total time spent in processing Reference objects. [Ref Enq: 0.0 ms] Time spent in enqueuing references to the ReferenceQueues. [Free CSet: 0.3 ms] Time spent in freeing the collection set data structure. [Eden: 12M(12M)->0B(13M) Survivors: 0B->2048K Heap: 14M(64M)->9739K(64M)] This line gives the details on the heap size changes with the Evacuation Pause. This shows that Eden had the occupancy of 12M and its capacity was also 12M before the collection. After the collection, its occupancy got reduced to 0 since everything is evacuated/promoted from Eden during a collection, and its target size grew to 13M. The new Eden capacity of 13M is not reserved at this point. This value is the target size of the Eden. Regions are added to Eden as the demand is made and when the added regions reach to the target size, we start the next collection. Similarly, Survivors had the occupancy of 0 bytes and it grew to 2048K after the collection. The total heap occupancy and capacity was 14M and 64M receptively before the collection and it became 9739K and 64M after the collection. Apart from the evacuation pauses, G1 also performs concurrent-marking to build the live data information of regions. 1.416: [GC pause (young) (initial-mark), 0.62417980 secs] ….... 2.042: [GC concurrent-root-region-scan-start] 2.067: [GC concurrent-root-region-scan-end, 0.0251507] 2.068: [GC concurrent-mark-start] 3.198: [GC concurrent-mark-reset-for-overflow] 4.053: [GC concurrent-mark-end, 1.9849672 sec] 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.090: [GC concurrent-cleanup-start] 4.091: [GC concurrent-cleanup-end, 0.0002721] The first phase of a marking cycle is Initial Marking where all the objects directly reachable from the roots are marked and this phase is piggy-backed on a fully young Evacuation Pause. 2.042: [GC concurrent-root-region-scan-start] This marks the start of a concurrent phase that scans the set of root-regions which are directly reachable from the survivors of the initial marking phase. 2.067: [GC concurrent-root-region-scan-end, 0.0251507] End of the concurrent root region scan phase and it lasted for 0.0251507 seconds. 2.068: [GC concurrent-mark-start] Start of the concurrent marking at 2.068 secs from the start of the process. 3.198: [GC concurrent-mark-reset-for-overflow] This indicates that the global marking stack had became full and there was an overflow of the stack. Concurrent marking detected this overflow and had to reset the data structures to start the marking again. 4.053: [GC concurrent-mark-end, 1.9849672 sec] End of the concurrent marking phase and it lasted for 1.9849672 seconds. 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] This corresponds to the remark phase which is a stop-the-world phase. It completes the left over marking work (SATB buffers processing) from the previous phase. In this case, this phase took 0.0030184 secs and out of which 0.0000254 secs were spent on Reference processing. 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] Cleanup phase which is again a stop-the-world phase. It goes through the marking information of all the regions, computes the live data information of each region, resets the marking data structures and sorts the regions according to their gc-efficiency. In this example, the total heap size is 138M and after the live data counting it was found that the total live data size dropped down from 117M to 106M. 4.090: [GC concurrent-cleanup-start] This concurrent cleanup phase frees up the regions that were found to be empty (didn't contain any live data) during the previous stop-the-world phase. 4.091: [GC concurrent-cleanup-end, 0.0002721] Concurrent cleanup phase took 0.0002721 secs to free up the empty regions. Option -XX:G1PrintRegionLivenessInfo Now, let's look at the output generated with the flag G1PrintRegionLivenessInfo. This is a diagnostic option and gets enabled with -XX:+UnlockDiagnosticVMOptions. G1PrintRegionLivenessInfo prints the live data information of each region during the Cleanup phase of the concurrent-marking cycle. 26.896: [GC cleanup ### PHASE Post-Marking @ 26.896### HEAP committed: 0x02e00000-0x0fe00000 reserved: 0x02e00000-0x12e00000 region-size: 1048576 Cleanup phase of the concurrent-marking cycle started at 26.896 secs from the start of the process and this live data information is being printed after the marking phase. Committed G1 heap ranges from 0x02e00000 to 0x0fe00000 and the total G1 heap reserved by JVM is from 0x02e00000 to 0x12e00000. Each region in the G1 heap is of size 1048576 bytes. ### type address-range used prev-live next-live gc-eff### (bytes) (bytes) (bytes) (bytes/ms) This is the header of the output that tells us about the type of the region, address-range of the region, used space in the region, live bytes in the region with respect to the previous marking cycle, live bytes in the region with respect to the current marking cycle and the GC efficiency of that region. ### FREE 0x02e00000-0x02f00000 0 0 0 0.0 This is a Free region. ### OLD 0x02f00000-0x03000000 1048576 1038592 1038592 0.0 Old region with address-range from 0x02f00000 to 0x03000000. Total used space in the region is 1048576 bytes, live bytes as per the previous marking cycle are 1038592 and live bytes with respect to the current marking cycle are also 1038592. The GC efficiency has been computed as 0. ### EDEN 0x03400000-0x03500000 20992 20992 20992 0.0 This is an Eden region. ### HUMS 0x0ae00000-0x0af00000 1048576 1048576 1048576 0.0### HUMC 0x0af00000-0x0b000000 1048576 1048576 1048576 0.0### HUMC 0x0b000000-0x0b100000 1048576 1048576 1048576 0.0### HUMC 0x0b100000-0x0b200000 1048576 1048576 1048576 0.0### HUMC 0x0b200000-0x0b300000 1048576 1048576 1048576 0.0### HUMC 0x0b300000-0x0b400000 1048576 1048576 1048576 0.0### HUMC 0x0b400000-0x0b500000 1001480 1001480 1001480 0.0 These are the continuous set of regions called Humongous regions for storing a large object. HUMS (Humongous starts) marks the start of the set of humongous regions and HUMC (Humongous continues) tags the subsequent regions of the humongous regions set. ### SURV 0x09300000-0x09400000 16384 16384 16384 0.0 This is a Survivor region. ### SUMMARY capacity: 208.00 MB used: 150.16 MB / 72.19 % prev-live: 149.78 MB / 72.01 % next-live: 142.82 MB / 68.66 % At the end, a summary is printed listing the capacity, the used space and the change in the liveness after the completion of concurrent marking. In this case, G1 heap capacity is 208MB, total used space is 150.16MB which is 72.19% of the total heap size, live data in the previous marking was 149.78MB which was 72.01% of the total heap size and the live data as per the current marking is 142.82MB which is 68.66% of the total heap size. Option -XX:+G1PrintHeapRegions G1PrintHeapRegions option logs the regions related events when regions are committed, allocated into or are reclaimed. COMMIT/UNCOMMIT events G1HR COMMIT [0x6e900000,0x6ea00000]G1HR COMMIT [0x6ea00000,0x6eb00000] Here, the heap is being initialized or expanded and the region (with bottom: 0x6eb00000 and end: 0x6ec00000) is being freshly committed. COMMIT events are always generated in order i.e. the next COMMIT event will always be for the uncommitted region with the lowest address. G1HR UNCOMMIT [0x72700000,0x72800000]G1HR UNCOMMIT [0x72600000,0x72700000] Opposite to COMMIT. The heap got shrunk at the end of a Full GC and the regions are being uncommitted. Like COMMIT, UNCOMMIT events are also generated in order i.e. the next UNCOMMIT event will always be for the committed region with the highest address. GC Cycle events G1HR #StartGC 7G1HR CSET 0x6e900000G1HR REUSE 0x70500000G1HR ALLOC(Old) 0x6f800000G1HR RETIRE 0x6f800000 0x6f821b20G1HR #EndGC 7 This shows start and end of an Evacuation pause. This event is followed by a GC counter tracking both evacuation pauses and Full GCs. Here, this is the 7th GC since the start of the process. G1HR #StartFullGC 17G1HR UNCOMMIT [0x6ed00000,0x6ee00000]G1HR POST-COMPACTION(Old) 0x6e800000 0x6e854f58G1HR #EndFullGC 17 Shows start and end of a Full GC. This event is also followed by the same GC counter as above. This is the 17th GC since the start of the process. ALLOC events G1HR ALLOC(Eden) 0x6e800000 The region with bottom 0x6e800000 just started being used for allocation. In this case it is an Eden region and allocated into by a mutator thread. G1HR ALLOC(StartsH) 0x6ec00000 0x6ed00000G1HR ALLOC(ContinuesH) 0x6ed00000 0x6e000000 Regions being used for the allocation of Humongous object. The object spans over two regions. G1HR ALLOC(SingleH) 0x6f900000 0x6f9eb010 Single region being used for the allocation of Humongous object. G1HR COMMIT [0x6ee00000,0x6ef00000]G1HR COMMIT [0x6ef00000,0x6f000000]G1HR COMMIT [0x6f000000,0x6f100000]G1HR COMMIT [0x6f100000,0x6f200000]G1HR ALLOC(StartsH) 0x6ee00000 0x6ef00000G1HR ALLOC(ContinuesH) 0x6ef00000 0x6f000000G1HR ALLOC(ContinuesH) 0x6f000000 0x6f100000G1HR ALLOC(ContinuesH) 0x6f100000 0x6f102010 Here, Humongous object allocation request could not be satisfied by the free committed regions that existed in the heap, so the heap needed to be expanded. Thus new regions are committed and then allocated into for the Humongous object. G1HR ALLOC(Old) 0x6f800000 Old region started being used for allocation during GC. G1HR ALLOC(Survivor) 0x6fa00000 Region being used for copying old objects into during a GC. Note that Eden and Humongous ALLOC events are generated outside the GC boundaries and Old and Survivor ALLOC events are generated inside the GC boundaries. Other Events G1HR RETIRE 0x6e800000 0x6e87bd98 Retire and stop using the region having bottom 0x6e800000 and top 0x6e87bd98 for allocation. Note that most regions are full when they are retired and we omit those events to reduce the output volume. A region is retired when another region of the same type is allocated or we reach the start or end of a GC(depending on the region). So for Eden regions: For example: 1. ALLOC(Eden) Foo2. ALLOC(Eden) Bar3. StartGC At point 2, Foo has just been retired and it was full. At point 3, Bar was retired and it was full. If they were not full when they were retired, we will have a RETIRE event: 1. ALLOC(Eden) Foo2. RETIRE Foo top3. ALLOC(Eden) Bar4. StartGC G1HR CSET 0x6e900000 Region (bottom: 0x6e900000) is selected for the Collection Set. The region might have been selected for the collection set earlier (i.e. when it was allocated). However, we generate the CSET events for all regions in the CSet at the start of a GC to make sure there's no confusion about which regions are part of the CSet. G1HR POST-COMPACTION(Old) 0x6e800000 0x6e839858 POST-COMPACTION event is generated for each non-empty region in the heap after a full compaction. A full compaction moves objects around, so we don't know what the resulting shape of the heap is (which regions were written to, which were emptied, etc.). To deal with this, we generate a POST-COMPACTION event for each non-empty region with its type (old/humongous) and the heap boundaries. At this point we should only have Old and Humongous regions, as we have collapsed the young generation, so we should not have eden and survivors. POST-COMPACTION events are generated within the Full GC boundary. G1HR CLEANUP 0x6f400000G1HR CLEANUP 0x6f300000G1HR CLEANUP 0x6f200000 These regions were found empty after remark phase of Concurrent Marking and are reclaimed shortly afterwards. G1HR #StartGC 5G1HR CSET 0x6f400000G1HR CSET 0x6e900000G1HR REUSE 0x6f800000 At the end of a GC we retire the old region we are allocating into. Given that its not full, we will carry on allocating into it during the next GC. This is what REUSE means. In the above case 0x6f800000 should have been the last region with an ALLOC(Old) event during the previous GC and should have been retired before the end of the previous GC. G1HR ALLOC-FORCE(Eden) 0x6f800000 A specialization of ALLOC which indicates that we have reached the max desired number of the particular region type (in this case: Eden), but we decided to allocate one more. Currently it's only used for Eden regions when we extend the young generation because we cannot do a GC as the GC-Locker is active. G1HR EVAC-FAILURE 0x6f800000 During a GC, we have failed to evacuate an object from the given region as the heap is full and there is no space left to copy the object. This event is generated within GC boundaries and exactly once for each region from which we failed to evacuate objects. When Heap Regions are reclaimed ? It is also worth mentioning when the heap regions in the G1 heap are reclaimed. All regions that are in the CSet (the ones that appear in CSET events) are reclaimed at the end of a GC. The exception to that are regions with EVAC-FAILURE events. All regions with CLEANUP events are reclaimed. After a Full GC some regions get reclaimed (the ones from which we moved the objects out). But that is not shown explicitly, instead the non-empty regions that are left in the heap are printed out with the POST-COMPACTION events.

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