hprof | Heap profile reader for Go

So I can't get Android Studio to open through the studio64.exe launcher.

It was working perfectly just a few days ago and now it won't launch. Tried uninstalling and installing the latest Bumblebee 2021.1 with no luck. Tried deleting the Android studio files in AppData but still no luck. Even tried reverting to an older restore point with no success.

I have already set JDK_HOME and JAVA_HOME to the included Android Studio jre. After doing this the app now launches by running studio.bat but the actual launcher still fails. It just shows up for a brief second in Task Manager then disappears. No error messages or anything, just blank.

The weird thing is that I also have Intellij IDEA but that launches perfectly fine through it's launcher. Just Android Studio that is giving me issues.

Any help will be appreciated!

Edit: Attaching the log from the IDE.

I took over a JAVA-WEB based SOA system recently and it doesn't runs that well untill now. One of the springboot applications will take up up to 100% of the CPU use. By using jastack I get to know that most of the Cpu use was made by GC threads, for there are something in jvm that cannot be collected and removed. I made the dump and the hprof file was about 20Gbk in size,Which seems much too big.

By using Jprofiler I happen to know that there are a lot of of hashmap entries,aprroximately 80,635,782 instances in total(showed as follows).
Jprofiler Heapwalker results So there must be some meomery leaks among theses Hashmap entries(Maybe the un-proper keys).But too many instances so it is hard to find the right place where memeory leak happens.(Maybe I havnt find the right way to use Jprofiler)too many instances to find.

I'd appreciate it if you can help , how to do with so many instances.THKS!

I am using elasticsearch 5.6.13 version, I need some experts configurations for the elasticsearch. I have 3 nodes in the same system (node1,node2,node3) where node1 is master and else 2 data nodes. I have number of indexes around 40, I created all these indexes with default 5 primary shards and some of them have 2 replicas. What I am facing the issue right now, My data (scraping) is growing day by day and I have 400GB of the data in my one of index. similarly 3 other indexes are also very loaded. From some last days I am facing the issue while insertion of data my elasticsearch hangs and then the service is killed which effect my processing. I have tried several things. I am sharing the system specs and current ES configuration + logs. Please suggest some solution.

The System Specs: RAM: 160 GB, CPU: AMD EPYC 7702P 64-Core Processor, Drive: 2 TB SSD (The drive in which the ES installed still have 500 GB left)

ES Configuration JVM options: -Xms26g, -Xmx26g (I just try this but not sure what is the perfect heap size for my scenario) I just edit this above lines and the rest of the file is as defult. I edit this on all three nodes jvm.options files.

ES LOGS

[2021-09-22T12:05:17,983][WARN ][o.e.m.j.JvmGcMonitorService] [sashanode1] [gc][170] overhead, spent [7.1s] collecting in the last [7.2s] [2021-09-22T12:05:21,868][WARN ][o.e.m.j.JvmGcMonitorService] [sashanode1] [gc][171] overhead, spent [3.7s] collecting in the last [1.9s] [2021-09-22T12:05:51,190][WARN ][o.e.m.j.JvmGcMonitorService] [sashanode1] [gc][172] overhead, spent [27.7s] collecting in the last [23.3s] [2021-09-22T12:06:54,629][WARN ][o.e.m.j.JvmGcMonitorService] [cluster_name] [gc][173] overhead, spent [57.5s] collecting in the last [1.1m] [2021-09-22T12:06:56,536][WARN ][o.e.m.j.JvmGcMonitorService] [cluster_name] [gc][174] overhead, spent [1.9s] collecting in the last [1.9s] [2021-09-22T12:07:02,176][WARN ][o.e.m.j.JvmGcMonitorService] [cluster_name] [gc][175] overhead, spent [5.4s] collecting in the last [5.6s] [2021-09-22T12:06:56,546][ERROR][o.e.i.e.Engine ] [cluster_name] [index_name][3] merge failed java.lang.OutOfMemoryError: Java heap space

[2021-09-22T12:06:56,548][ERROR][o.e.b.ElasticsearchUncaughtExceptionHandler] [cluster_name] fatal error in thread [elasticsearch[cluster_name][bulk][T#25]], exiting java.lang.OutOfMemoryError: Java heap space

Some more logs

[2021-09-22T12:10:06,526][INFO ][o.e.n.Node ] [cluster_name] initializing ... [2021-09-22T12:10:06,589][INFO ][o.e.e.NodeEnvironment ] [cluster_name] using [1] data paths, mounts [[(D:)]], net usable_space [563.3gb], net total_space [1.7tb], spins? [unknown], types [NTFS] [2021-09-22T12:10:06,589][INFO ][o.e.e.NodeEnvironment ] [cluster_name] heap size [1.9gb], compressed ordinary object pointers [true] [2021-09-22T12:10:07,239][INFO ][o.e.n.Node ] [cluster_name] node name [sashanode1], node ID [2p-ux-OXRKGuxmN0efvF9Q] [2021-09-22T12:10:07,240][INFO ][o.e.n.Node ] [cluster_name] version[5.6.13], pid[57096], build[4d5320b/2018-10-30T19:05:08.237Z], OS[Windows Server 2019/10.0/amd64], JVM[Oracle Corporation/Java HotSpot(TM) 64-Bit Server VM/1.8.0_261/25.261-b12] [2021-09-22T12:10:07,240][INFO ][o.e.n.Node ] [cluster_name] JVM arguments [-Xms2g, -Xmx2g, -XX:+UseConcMarkSweepGC, -XX:CMSInitiatingOccupancyFraction=75, -XX:+UseCMSInitiatingOccupancyOnly, -XX:+AlwaysPreTouch, -Xss1m, -Djava.awt.headless=true, -Dfile.encoding=UTF-8, -Djna.nosys=true, -Djdk.io.permissionsUseCanonicalPath=true, -Dio.netty.noUnsafe=true, -Dio.netty.noKeySetOptimization=true, -Dio.netty.recycler.maxCapacityPerThread=0, -Dlog4j.shutdownHookEnabled=false, -Dlog4j2.disable.jmx=true, -Dlog4j.skipJansi=true, -XX:+HeapDumpOnOutOfMemoryError, -Delasticsearch, -Des.path.home=D:\Databases\ES\elastic and kibana 5.6.13\es_node_1, -Des.default.path.logs=D:\Databases\ES\elastic and kibana 5.6.13\es_node_1\logs, -Des.default.path.data=D:\Databases\ES\elastic and kibana 5.6.13\es_node_1\data, -Des.default.path.conf=D:\Databases\ES\elastic and kibana 5.6.13\es_node_1\config, exit, -Xms2048m, -Xmx2048m, -Xss1024k]

Also in my ES folder there are so many files with the random names (java_pid197036.hprof) Further details can be shared please suggest any further configurations. Thanks

The output for _cluster/stats?pretty&human is

{ "_nodes": { "total": 3, "successful": 3, "failed": 0 }, "cluster_name": "cluster_name", "timestamp": 1632375228033, "status": "red", "indices": { "count": 42, "shards": { "total": 508, "primaries": 217, "replication": 1.3410138248847927, "index": { "shards": { "min": 2, "max": 60, "avg": 12.095238095238095 }, "primaries": { "min": 1, "max": 20, "avg": 5.166666666666667 }, "replication": { "min": 1.0, "max": 2.0, "avg": 1.2857142857142858 } } }, "docs": { "count": 107283077, "deleted": 1047418 }, "store": { "size": "530.2gb", "size_in_bytes": 569385384976, "throttle_time": "0s", "throttle_time_in_millis": 0 }, "fielddata": { "memory_size": "0b", "memory_size_in_bytes": 0, "evictions": 0 }, "query_cache": { "memory_size": "0b", "memory_size_in_bytes": 0, "total_count": 0, "hit_count": 0, "miss_count": 0, "cache_size": 0, "cache_count": 0, "evictions": 0 }, "completion": { "size": "0b", "size_in_bytes": 0 }, "segments": { "count": 3781, "memory": "2gb", "memory_in_bytes": 2174286255, "terms_memory": "1.7gb", "terms_memory_in_bytes": 1863786029, "stored_fields_memory": "105.6mb", "stored_fields_memory_in_bytes": 110789048, "term_vectors_memory": "0b", "term_vectors_memory_in_bytes": 0, "norms_memory": "31.9mb", "norms_memory_in_bytes": 33527808, "points_memory": "13.1mb", "points_memory_in_bytes": 13742470, "doc_values_memory": "145.3mb", "doc_values_memory_in_bytes": 152440900, "index_writer_memory": "0b", "index_writer_memory_in_bytes": 0, "version_map_memory": "0b", "version_map_memory_in_bytes": 0, "fixed_bit_set": "0b", "fixed_bit_set_memory_in_bytes": 0, "max_unsafe_auto_id_timestamp": 1632340789677, "file_sizes": { } } }, "nodes": { "count": { "total": 3, "data": 3, "coordinating_only": 0, "master": 1, "ingest": 3 }, "versions": [ "5.6.13" ], "os": { "available_processors": 192, "allocated_processors": 96, "names": [ { "name": "Windows Server 2019", "count": 3 } ], "mem": { "total": "478.4gb", "total_in_bytes": 513717497856, "free": "119.7gb", "free_in_bytes": 128535437312, "used": "358.7gb", "used_in_bytes": 385182060544, "free_percent": 25, "used_percent": 75 } }, "process": { "cpu": { "percent": 5 }, "open_file_descriptors": { "min": -1, "max": -1, "avg": 0 } }, "jvm": { "max_uptime": "1.9d", "max_uptime_in_millis": 167165106, "versions": [ { "version": "1.8.0_261", "vm_name": "Java HotSpot(TM) 64-Bit Server VM", "vm_version": "25.261-b12", "vm_vendor": "Oracle Corporation", "count": 3 } ], "mem": { "heap_used": "5gb", "heap_used_in_bytes": 5460944144, "heap_max": "5.8gb", "heap_max_in_bytes": 6227755008 }, "threads": 835 }, "fs": { "total": "1.7tb", "total_in_bytes": 1920365228032, "free": "499.1gb", "free_in_bytes": 535939969024, "available": "499.1gb", "available_in_bytes": 535939969024 }, "plugins": [ ], "network_types": { "transport_types": { "netty4": 3 }, "http_types": { "netty4": 3 } } } }

The jvm.options file.

I'm using spring boot 2.5.6 and I'm generating the docker image with the spring boot maven plugin. I'm deploying the application using AWS EKS with nodes managed by fargate.

The plugin configuration is the following

I've heap dump file testdump.hprof. I parsed this file using below command.

./ParseHeapDump.sh /home/rajkumar/Documents/heap-dump-ads03/testdump.hprof

The above command generated the below files.

testdump.threads

testdump.idx.index

testdump.o2c.index

testdump.a2s.index

testdump.inbound.index

testdump.outbound.index

testdump.o2hprof.index

testdump.index

testdump.domIn.index

testdump.o2ret.index

testdump.domOut.index

I've installed eclipse memory analyzer plugin im my eclipse IDE. I don't know how to open the index files in IDE for analyzing. I opened the index file directly but it shows some binary string.

Any idea how can I open the index files in the eclipse?

While I am running my test both from GUI and non-GUI, observing out of memory error and JMeter generate e HPROF file as the dump. How is analyze this file ?

I am little confused with how to pass the arguments as REST API JSON.

Consider below spark submit command.

The goal is to have a Spark Streaming application that read data from Kafka and use Delta Lake to create store data. The granularity of the delta table is pretty granular, the first partition is the organization_id (there are more than 5000 organizations) and the second partition is the date.

The application has a expected latency, but it does not last more than one day up. The error is always about memory as I'll show below.

OpenJDK 64-Bit Server VM warning: INFO: os::commit_memory(0x00000006f8000000, 671088640, 0) failed; error='Cannot allocate memory' (errno=12)

There is no persistence and the memory is already high for the whole application.

Increasing memory and workes were the first things I've tried, but the number of partitions were changed as well, from 4 to 16.

Okay, this problem is driving me up a wall, I can't figure out why Prometheus won't serve metrics. I got to 192.168.2.13:8534/metrics but all I get is the spinner contacting the port. I go to "wget http://localhost:8055" locally inside the container and I get

"Connecting to localhost (localhost)|127.0.0.1|:8055... connected. HTTP request sent, awaiting response..."

Docker is pointing 8543 -> 8055

I call my app to start which is nothing more than a class with Main method. With the call below my class app starts and responds perfectly. I also open JVisualVM and JMX show all the JVM info and metrics perfectly. I can attach a debugger no problem.