One request of rampUsers() is not recorded.
Eg. when I do a create.inject(rampUsers(10) during (5 seconds)).protocols(protocol)
Simulation mock.CatsKarateSimulation started...
================================================================================
2019-04-22 15:59:37 4s elapsed
---- Requests ------------------------------------------------------------------
> Global (OK=9 KO=0 )
> POST /cats (OK=9 KO=0 )
---- create --------------------------------------------------------------------
[##########################################################################]100%
waiting: 0 / active: 0 / done: 10
================================================================================
Simulation mock.CatsKarateSimulation completed in 4 seconds
15:59:42.512 [GatlingSystem-akka.actor.default-dispatcher-5] ERROR com.intuit.karate - http request failed: Ask timed out on [Actor[akka://GatlingSystem/user/karate-68#-1547527748]] afte
r [5100 ms]. Message of type [scala.concurrent.duration.FiniteDuration]. A typical reason for `AskTimeoutException` is that the recipient actor didn't send a reply.
Parsing log file(s)...
Parsing log file(s) done
Generating reports...
================================================================================
---- Global Information --------------------------------------------------------
> request count 9 (OK=9 KO=0 )
> min response time 6 (OK=6 KO=- )
> max response time 153 (OK=153 KO=- )
> mean response time 23 (OK=23 KO=- )
> std deviation 46 (OK=46 KO=- )
> response time 50th percentile 7 (OK=7 KO=- )
> response time 75th percentile 8 (OK=8 KO=- )
> response time 95th percentile 95 (OK=95 KO=- )
> response time 99th percentile 141 (OK=141 KO=- )
> mean requests/sec 1.8 (OK=1.8 KO=- )
---- Response Time Distribution ------------------------------------------------
> t < 800 ms 9 (100%)
> 800 ms < t < 1200 ms 0 ( 0%)
> t > 1200 ms 0 ( 0%)
> failed 0 ( 0%)
================================================================================
Reports generated in 1s.
There should be 10 response recorded. Instead I only receive 9 responses.
Also, atOnceUsers() would not send the requests or generate a report. I read the issue at https://github.com/intuit/karate/issues/721, and the issues might be connected.
Yes, can you build from source and see if it solves the problem:
https://github.com/intuit/karate/wiki/Developer-Guide
EDIT: we feel we have solved this, refer the issue you linked for details: https://github.com/intuit/karate/issues/721
Related
I was wondering if anyone can tell me what these mean. From most people posting about them, there is no more than double digits. However, I have 1051556645921812989870080 Media and Data Integrity Errors on my SK hynix PC711 on my new HP dev one. Thanks!
Here's my entire smartctl output
`smartctl 7.3 2022-02-28 r5338 [x86_64-linux-6.0.7-arch1-1] (local build)
Copyright (C) 2002-22, Bruce Allen, Christian Franke, www.smartmontools.org
=== START OF INFORMATION SECTION ===
Model Number: SK hynix PC711 HFS001TDE9X073N
Serial Number: KDB3N511010503A37
Firmware Version: HPS0
PCI Vendor/Subsystem ID: 0x1c5c
IEEE OUI Identifier: 0xace42e
Total NVM Capacity: 1,024,209,543,168 [1.02 TB]
Unallocated NVM Capacity: 0
Controller ID: 1
NVMe Version: 1.3
Number of Namespaces: 1
Namespace 1 Size/Capacity: 1,024,209,543,168 [1.02 TB]
Namespace 1 Formatted LBA Size: 512
Namespace 1 IEEE EUI-64: ace42e 00254f98f1
Local Time is: Wed Nov 9 13:58:37 2022 EST
Firmware Updates (0x16): 3 Slots, no Reset required
Optional Admin Commands (0x001f): Security Format Frmw_DL NS_Mngmt Self_Test
Optional NVM Commands (0x005f): Comp Wr_Unc DS_Mngmt Wr_Zero Sav/Sel_Feat Timestmp
Log Page Attributes (0x1e): Cmd_Eff_Lg Ext_Get_Lg Telmtry_Lg Pers_Ev_Lg
Maximum Data Transfer Size: 64 Pages
Warning Comp. Temp. Threshold: 84 Celsius
Critical Comp. Temp. Threshold: 85 Celsius
Namespace 1 Features (0x02): NA_Fields
Supported Power States
St Op Max Active Idle RL RT WL WT Ent_Lat Ex_Lat
0 + 6.3000W - - 0 0 0 0 5 5
1 + 2.4000W - - 1 1 1 1 30 30
2 + 1.9000W - - 2 2 2 2 100 100
3 - 0.0500W - - 3 3 3 3 1000 1000
4 - 0.0040W - - 3 3 3 3 1000 9000
Supported LBA Sizes (NSID 0x1)
Id Fmt Data Metadt Rel_Perf
0 + 512 0 0
1 - 4096 0 0
=== START OF SMART DATA SECTION ===
SMART overall-health self-assessment test result: PASSED
SMART/Health Information (NVMe Log 0x02)
Critical Warning: 0x00
Temperature: 34 Celsius
Available Spare: 100%
Available Spare Threshold: 5%
Percentage Used: 0%
Data Units Read: 13,162,025 [6.73 TB]
Data Units Written: 3,846,954 [1.96 TB]
Host Read Commands: 156,458,059
Host Write Commands: 128,658,566
Controller Busy Time: 116
Power Cycles: 273
Power On Hours: 126
Unsafe Shutdowns: 15
Media and Data Integrity Errors: 1051556645921812989870080
Error Information Log Entries: 0
Warning Comp. Temperature Time: 0
Critical Comp. Temperature Time: 0
Temperature Sensor 1: 34 Celsius
Temperature Sensor 2: 36 Celsius
Error Information (NVMe Log 0x01, 16 of 256 entries)
No Errors Logged`
Encountered a similar SMART reading from the same model.
I'm seeing a reported Media and Data Integrity Errors rate of a value that's over 2 ^ 84.
It could just be an error with its SMART implementation or the utility reading from it.
Converting your reported value of 1051556645921812989870080 to hex, we get 0xdead0000000000000000 big endian and 0x0000000000000000adde little endian.
Similarly, when I convert my value to hex, I get 0xffff0000000000000000 big endian and 0x0000000000000000ffff little endian, where f is just denotes a value other than 0.
I'm going to assume that the Media and Data Integrity Errors value has no actual meaning with regard to real errors. I doubt that both of us would have values that are padded with 16 0's when converted to hex. Something is sending/receiving/parsing bad data.
If you poke around the other reported SMART values in your post, and on my end, some of them don't seem to make much sense, either.
I am analysing the amount of hashes cracked over a set period of time.
I am looking to save the current status of the crack every 10 seconds.
'''
Recovered........: 132659/296112 (44.80%) Digests, 0/1 (0.00%) Salts
Recovered/Time...: CUR:3636,N/A,N/A AVG:141703,8502198,204052756 (Min,Hour,Day)
Progress.........: 15287255040/768199139595 (1.99%)
'''
I want these 3 lines of the status saved every 10 seconds or so.
Is it possible to do this within hashcat or will I need to make a separate script in python?
Getting the status every 10 seconds
You can enable printing the status with --status and you can set the status to prints every X seconds with --status-timer X. You can see these command line arguments on the hashcat options wiki page, or hashcat --help.
Example: hashcat -a 0 -m 0 example.hash example.dict --status --status-timer 10
Saving all the statuses
I'm assuming that you just want to save everything that gets printed by hashcat while it's running. An easy way to do this is just copy everything from stdout into a file. This is a popular s/o question, so we'll just use this answer.
To be safe, let's use -a which appends to the file, so we don't accidentally overwrite previous runs. All we need to do is put | tee -a file.txt after our hashcat call.
Solution
Give this a shot, it should save all the statuses (and everything else from stdout) to output.txt:
hashcat -a A -m M hashes.txt dictionary.txt --status --status-timer 10 | tee -a output.txt
Just swap out A, M, hashes.txt, and dictionary.txt with the arguments you're using.
If you need help getting just the "Recovered" lines from this output file, or if this doesn't work on your computer (I'm on OSX), let me know in a comment.
In addition to Andrew Zick's answer, note that for machine-readable status, hashcat has native support for machine-readable output - see the --machine-readable option. This produces tab-separated output like so:
STATUS 5 SPEED 111792 1000 EXEC_RUNTIME 0.007486 CURKU 1 PROGRESS 62 62 RECHASH 0 1 RECSALT 0 1 REJECTED 0 UTIL -1
STATUS 5 SPEED 14247323 1000 EXEC_RUNTIME 0.038953 CURKU 36 PROGRESS 2232 2232 RECHASH 0 1 RECSALT 0 1 REJECTED 0 UTIL -1
STATUS 5 SPEED 36929864 1000 EXEC_RUNTIME 1.661804 CURKU 1296 PROGRESS 80352 80352 RECHASH 0 1 RECSALT 0 1 REJECTED 0 UTIL -1
STATUS 5 SPEED 66538858 1000 EXEC_RUNTIME 3.237319 CURKU 46656 PROGRESS 28926722892672 RECHASH 0 1 RECSALT 0 1 REJECTED 0 UTIL -1
STATUS 5 SPEED 63562975 1000 EXEC_RUNTIME 3.480536 CURKU 1679616 PROGRESS 104136192 104136192 RECHASH 0 1 RECSALT 0 1 REJECTED 0 UTIL -1
... which is exactly what tools like Hashtopolis use to provide a front-end to hashcat output.
For machine-readable output, the options --outfile, and --outfile-format are available. See the Format section of the output of hashcat --help for the options to --outfile-format:
- [ Outfile Formats ] -
# | Format
===+========
1 | hash[:salt]
2 | plain
3 | hex_plain
4 | crack_pos
5 | timestamp absolute
6 | timestamp relative
We recently migrated from MapReduce to TEZ for executing Hive queries on EMR. We are seeing cases where for the exact hive query launches very different number of mappers. See Map 3 phase below. On the first run it requested for 305 resources and on another run it requested for 4534 mappers. ( Please ignore the KILLED status because I manually killed the query.) Why does this happen ? How can we change it to be based on underlying data size instead ?
Run 1
----------------------------------------------------------------------------------------------
VERTICES MODE STATUS TOTAL COMPLETED RUNNING PENDING FAILED KILLED
----------------------------------------------------------------------------------------------
Map 1 container KILLED 5 0 0 5 0 0
Map 3 container KILLED 305 0 0 305 0 0
Map 5 container KILLED 16 0 0 16 0 0
Map 6 container KILLED 1 0 0 1 0 0
Reducer 2 container KILLED 333 0 0 333 0 0
Reducer 4 container KILLED 796 0 0 796 0 0
----------------------------------------------------------------------------------------------
VERTICES: 00/06 [>>--------------------------] 0% ELAPSED TIME: 14.16 s
----------------------------------------------------------------------------------------------
Run 2
----------------------------------------------------------------------------------------------
VERTICES MODE STATUS TOTAL COMPLETED RUNNING PENDING FAILED KILLED
----------------------------------------------------------------------------------------------
Map 1 .......... container SUCCEEDED 5 5 0 0 0 0
Map 3 container KILLED 4534 0 0 4534 0 0
Map 5 .......... container SUCCEEDED 325 325 0 0 0 0
Map 6 .......... container SUCCEEDED 1 1 0 0 0 0
Reducer 2 container KILLED 333 0 0 333 0 0
Reducer 4 container KILLED 796 0 0 796 0 0
----------------------------------------------------------------------------------------------
VERTICES: 03/06 [=>>-------------------------] 5% ELAPSED TIME: 527.16 s
----------------------------------------------------------------------------------------------
This article explains the process in which Tez allocates resources. https://cwiki.apache.org/confluence/display/TEZ/How+initial+task+parallelism+works
If Tez grouping is enabled for the splits, then a generic grouping
logic is run on these splits to group them into larger splits. The
idea is to strike a balance between how parallel the processing is and
how much work is being done in each parallel process.
First, Tez tries to find out the resource availability in the cluster for these tasks. For that, YARN provides a headroom value (and
in future other attributes may be used). Lets say this value is T.
Next, Tez divides T with the resource per task (say M) to find out how many tasks can run in parallel at one (ie in a single wave). W =
T/M.
Next W is multiplied by a wave factor (from configuration - tez.grouping.split-waves) to determine the number of tasks to be used.
Lets say this value is N.
If there are a total of X splits (input shards) and N tasks then this would group X/N splits per task. Tez then estimates the size of
data per task based on the number of splits per task.
If this value is between tez.grouping.max-size & tez.grouping.min-size then N is accepted as the number of tasks. If
not, then N is adjusted to bring the data per task in line with the
max/min depending on which threshold was crossed.
For experimental purposes tez.grouping.split-count can be set in configuration to specify the desired number of groups. If this config
is specified then the above logic is ignored and Tez tries to group
splits into the specified number of groups. This is best effort.
After this the grouping algorithm is executed. It groups splits by node locality, then rack locality, while respecting the group size
limits.
I need to build a histogram, concerning DOMContentLoaded of a webpage. When I used BigQuery, I noticed that apart from density, there are 2 more attributes (start, end). In my head there should only be 1 attribute, the DOMContentLoaded event is only fired when the DOM has loaded.
Can anyone help clarify the difference of .start and .stop? These attributes always have 100 milliseconds difference between them (if start = X ms, then stop = X+100 ms. See a query example posted below.
I can not understand what these attributes represent exactly:
dom_content_loaded.histogram.bin.START
AND
dom_content_loaded.histogram.bin.END
Q: Which one of them represents the time that the DOMContentLoaded event
is fired in a user's browser?
SELECT
bin.START AS start,
bin.END AS endd
FROM
`chrome-ux-report.all.201809`,
UNNEST(dom_content_loaded.histogram.bin) AS bin
WHERE
origin = 'https://www.google.com'
Output:
Row |start | end
1 0 100
2 100 200
3 200 300
4 300 400
[...]
Below explains meaning of bin.start, bin.end and bin.density
Run below SELECT statement
SELECT
origin,
effective_connection_type.name type_name,
form_factor.name factor_name,
bin.start AS bin_start,
bin.end AS bin_end,
bin.density AS bin_density
FROM `chrome-ux-report.all.201809`,
UNNEST(dom_content_loaded.histogram.bin) AS bin
WHERE origin = 'https://www.google.com'
You will get 1550 rows in result
below are first 5 rows
Row origin type_name factor_name bin_start bin_end bin_density
1 https://www.google.com 4G phone 0 100 0.01065
2 https://www.google.com 4G phone 100 200 0.01065
3 https://www.google.com 4G phone 200 300 0.02705
4 https://www.google.com 4G phone 300 400 0.02705
5 https://www.google.com 4G phone 400 500 0.0225
You can read them as:
for phone with 4G load of dom_content was loaded within 100 milliseconds for 1.065% of loads; in between 100 and 200 milliseconds for 1.065%; in between 200 and 300 milliseconds for 2.705% and so on
To summarize for each origin, type and factor you got histogram that is represented as a repeated record with start and end of each bin along with density which represents percentage of respective user experience
Note: if you add up the dom_content_loaded densities across all dimensions for a single origin, you will get 1 (or a value very close to 1 due to approximations).
For example
SELECT SUM(bin.density) AS total_density
FROM `chrome-ux-report.all.201809`,
UNNEST(dom_content_loaded.histogram.bin) AS bin
WHERE origin = 'https://www.google.com'
returns
Row total_density
1 0.9995999999999978
Hope this helped
I am trying to create VRP file which defines a problem with time window and distance in seconds. I currently do not need capacity (can I turn it off?)
this is my file :
NAME: almirs-test
COMMENT: Generated for OptaPlanner Examples
TYPE: CVRPTW
DIMENSION: 2
EDGE_WEIGHT_TYPE: EXPLICIT
EDGE_WEIGHT_FORMAT: FULL_MATRIX
EDGE_WEIGHT_UNIT_OF_MEASUREMENT: sec
CAPACITY: 125
NODE_COORD_SECTION
0 0 0 BRUSSEL
55 1 1 ANTHISNES
EDGE_WEIGHT_SECTION
0.0 1
1 0.0
DEMAND_SECTION
0 0 0 100 0
55 1 0 10 1
DEPOT_SECTION
0
-1
EOF
it is corcectly parsed, and I see locations on screen, but when I try to solve it I get message : "Not feasible"
org.optaplanner.examples.vehiclerouting.solver/arrivalAfterDueTime/level0/[ANTHISNES]=-990
any idea what am I doing wrong? any samples where I can see how it is done?
thanks
almir