Add targets running OpenROAD GUI with Docker image

This PR adds *_gui targets for Docker flow, which has to be called with run, e.g.:
bazel run L1MetadataArray_full_final_gui

GUI for local flow works fine, apart from synthesis stage, which requires additional LEF files - new target *_gui_synth_make resolves this issue.

I am unable to get this to work from megaboom:
$ git diff | cat
diff --git a/.bazelrc b/.bazelrc
index 1fefebc..1cc1b92 100644
--- a/.bazelrc
+++ b/.bazelrc
@@ -1,2 +1,3 @@
 build --incompatible_strict_action_env
 build --spawn_strategy=local
+build --remote_cache=https://storage.googleapis.com/megaboom-bazel-artifacts --google_credentials=/home/oyvind/Downloads/innate-diode-408109-9c5d0543f9b3.json --remote_cache_compression=true
diff --git a/MODULE.bazel b/MODULE.bazel
index 84bf612..375ec83 100644
--- a/MODULE.bazel
+++ b/MODULE.bazel
@@ -5,12 +5,12 @@ module(
 )

 bazel_dep(name = "bazel-orfs")
-git_override(
-    module_name = "bazel-orfs",
-    remote = "https://github.com/The-OpenROAD-Project/bazel-orfs.git",
-    commit = "c4fc0c549fde78560f5504e823c1283895e1effe",
-)
-
-#local_path_override(
-#    module_name = "bazel-orfs", path = "../bazel-orfs"
+#git_override(
+#    module_name = "bazel-orfs",
+#    remote = "https://github.com/The-OpenROAD-Project/bazel-orfs.git",
+#    commit = "c4fc0c549fde78560f5504e823c1283895e1effe",
 #)
+
+local_path_override(
+    module_name = "bazel-orfs", path = "../bazel-orfs"
+)
diff --git a/MODULE.bazel.lock b/MODULE.bazel.lock
index 6d9b9cc..6855ca6 100644
--- a/MODULE.bazel.lock
+++ b/MODULE.bazel.lock
@@ -1,6 +1,6 @@
 {
   "lockFileVersion": 3,
-  "moduleFileHash": "13f80b1a5a0afc3c54e277230468d706e9635dd12bef30eb3dbad8571c1eac28",
+  "moduleFileHash": "c45e4d867d41f680d6d969336dcbebe781a17f6f3a7ee1435f0b87906b05754b",
   "flags": {
     "cmdRegistries": [
       "https://bcr.bazel.build/"
@@ -13,6 +13,7 @@
     "compatibilityMode": "ERROR"
   },
   "localOverrideHashes": {
+    "bazel-orfs": "2aca7cf8613c58b798ea6d8c170ebd5b597f1db83a21c7135f4a3925551c6506",
     "bazel_tools": "922ea6752dc9105de5af957f7a99a6933c0a6a712d23df6aad16a9c399f7e787"
   },
   "moduleDepGraph": {

Produces:
oyvind@small-cigar:~/megaboom$ bazel build BoomTile_synth_sdc
INFO: Invocation ID: 7906f391-5110-4930-8b9b-3887c2de15bc
INFO: Analyzed target //:BoomTile_synth_sdc (81 packages loaded, 387 targets configured).
ERROR: /home/oyvind/megaboom/BUILD.bazel:817:15: Executing genrule //:BoomTile_synth_sdc failed: (Exit 2): bash failed: error executing Genrule command (from target //:BoomTile_synth_sdc) /bin/bash -c ... (remaining 1 argument skipped)
++ uuidgen
+ uuid=6774601a-3e68-44be-9d9c-8df5ee143ef0
+++ dirname bazel-out/k8-opt-exec-ST-13d3ddad9198/bin/external/bazel-orfs~override/docker_shell
++ cd bazel-out/k8-opt-exec-ST-13d3ddad9198/bin/external/bazel-orfs~override
++ pwd
+ DIR=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-opt-exec-ST-13d3ddad9198/bin/external/bazel-orfs~override
++ pwd
+ WORKSPACE_ROOT=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../..
++ pwd
+ WORKSPACE_EXECROOT=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main
+ WORKSPACE_EXTERNAL=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../../external
+ XSOCK=/tmp/.X11-unix
+ XAUTH=/tmp/.docker.xauth
+ xauth nlist :0
+ sed -e 's/^..../ffff/'
+ xauth -f /tmp/.docker.xauth nmerge -
xauth:  unable to generate an authority file name
xauth:  /tmp/.docker.xauth not writable, changes will be ignored
xauth: (argv):1:  unable to read any entries from file "(stdin)"
+ ARGUMENTS='make bazel-synth_sdc elapsed'
+ test -t 0
+ export FLOW_HOME=/OpenROAD-flow-scripts/flow/
+ FLOW_HOME=/OpenROAD-flow-scripts/flow/
+++ find /home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main -maxdepth 1 -type l -exec realpath '{}' ';' -quit
++ dirname /home/oyvind/megaboom/floorplan_BoomTile_asap7_base_2024-04-16_23-53.tar.gz
+ export WORKSPACE_ORIGIN=/home/oyvind/megaboom
+ WORKSPACE_ORIGIN=/home/oyvind/megaboom
+ [[ external/bazel-orfs~override/synth_sdc-bazel.mk = external* ]]
+ export PATH_PREFIX=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../..
+ PATH_PREFIX=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../..
+ export MAKE_PATTERN_PREFIXED=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../../external/bazel-orfs~override/synth_sdc-bazel.mk
+ MAKE_PATTERN_PREFIXED=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../../external/bazel-orfs~override/synth_sdc-bazel.mk
+ [[ -n '' ]]
+ export DESIGN_CONFIG_PREFIXED=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_config.mk
+ DESIGN_CONFIG_PREFIXED=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_config.mk
+ export STAGE_CONFIG_PREFIXED=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_synth_sdc_config.mk
+ STAGE_CONFIG_PREFIXED=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_synth_sdc_config.mk
+ chmod -R +w /home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin
+ trap handle_sigterm SIGTERM
+ wait 27150
++ id -u
++ id -g
+ docker run --name bazel-orfs-6774601a-3e68-44be-9d9c-8df5ee143ef0 --rm -u 1000:1000 -e LIBGL_ALWAYS_SOFTWARE=1 -e QT_X11_NO_MITSHM=1 -e XDG_RUNTIME_DIR=/tmp/xdg-run -e DISPLAY= -e QT_XKB_CONFIG_ROOT=/usr/share/X11/xkb -v /tmp/.X11-unix:/tmp/.X11-unix -v /tmp/.docker.xauth:/tmp/.docker.xauth -e XAUTHORITY=/tmp/.docker.xauth -e BUILD_DIR=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main -e FLOW_HOME=/OpenROAD-flow-scripts/flow/ -e DESIGN_CONFIG=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_config.mk -e STAGE_CONFIG=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_synth_sdc_config.mk -e MAKE_PATTERN=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../../external/bazel-orfs~override/synth_sdc-bazel.mk -e MOCK_AREA_TCL= -e WORK_HOME=/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin -v /home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../..:/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../.. -v /home/oyvind/megaboom:/home/oyvind/megaboom --network host openroad/flow-ubuntu22.04-builder:latest bash -c 'set -ex
 . ./env.sh
 cd $FLOW_HOME
 make bazel-synth_sdc elapsed
 '
+ . ./env.sh
++ [[ linux-gnu == \d\a\r\w\i\n* ]]
++++ readlink -f ./env.sh
+++ dirname /OpenROAD-flow-scripts/env.sh
++ DIR=/OpenROAD-flow-scripts
++ '[' -f /opt/rh/rh-python38/enable ']'
++ export OPENROAD=/OpenROAD-flow-scripts/tools/OpenROAD
++ OPENROAD=/OpenROAD-flow-scripts/tools/OpenROAD
++ echo 'OPENROAD: /OpenROAD-flow-scripts/tools/OpenROAD'
++ export PATH=/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ PATH=/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ export PATH=/OpenROAD-flow-scripts/tools/install/yosys/bin:/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ PATH=/OpenROAD-flow-scripts/tools/install/yosys/bin:/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ export PATH=/OpenROAD-flow-scripts/tools/install/LSOracle/bin:/OpenROAD-flow-scripts/tools/install/yosys/bin:/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ PATH=/OpenROAD-flow-scripts/tools/install/LSOracle/bin:/OpenROAD-flow-scripts/tools/install/yosys/bin:/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ export PATH=/OpenROAD-flow-scripts/dependencies/bin:/OpenROAD-flow-scripts/tools/install/LSOracle/bin:/OpenROAD-flow-scripts/tools/install/yosys/bin:/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ PATH=/OpenROAD-flow-scripts/dependencies/bin:/OpenROAD-flow-scripts/tools/install/LSOracle/bin:/OpenROAD-flow-scripts/tools/install/yosys/bin:/OpenROAD-flow-scripts/tools/install/OpenROAD/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
++ [[ linux-gnu == \d\a\r\w\i\n* ]]
+ cd /OpenROAD-flow-scripts/flow/
+ make bazel-synth_sdc elapsed
/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/bazel-out/k8-fastbuild/bin/BoomTile_config.mk:16: /home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../../external/bazel-orfs~override/synth_sdc-bazel.mk: No such file or directory
make: *** No rule to make target '/home/oyvind/.cache/bazel/_bazel_oyvind/7e6ad621f3f951c3ee6f5b179289b54e/execroot/_main/../../external/bazel-orfs~override/synth_sdc-bazel.mk'.  Stop.
OPENROAD: /OpenROAD-flow-scripts/tools/OpenROAD
[INFO-FLOW] ASU ASAP7 - version 2
Default PVT selection: BC
Target //:BoomTile_synth_sdc failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 1.228s, Critical Path: 0.75s
INFO: 2 processes: 2 internal.
ERROR: Build did NOT complete successfully

This is forcing the use of docker for bazel run. I want to be able to choose between docker and a local ORFS.
I think it is fine to have _gui launch the docker, but I want to have a _gui_deps target that brings in the dependencies required to launch the gui and then use the _make script to launch the GUI using local ORFS.

Fails:
oyvind@small-cigar:~/bazel-orfs$ bazel run L1MetadataArray_full_final_gui
[deleted]
INFO: Elapsed time: 239.335s, Critical Path: 238.65s
INFO: 47 processes: 5 internal, 42 local.
INFO: Build completed successfully, 47 total actions
INFO: Running command line: bazel-bin/L1MetadataArray_full_final_gui.sh
/home/oyvind/.cache/bazel/_bazel_oyvind/6e078b44989a9ce1500a63165a20fd2a/execroot/_main/bazel-out/k8-fastbuild/bin/L1MetadataArray_full_final_gui.sh: line 1: bazel-out/k8-opt-exec-ST-13d3ddad9198/bin/docker_shell: No such file or directory

There were some conflicts with recently merged features, now it should work in both bazel-orfs and MegaBoom.
I also added *_open target for Docker flow and as requested *_gui_deps which build all dependencies needed to run GUI locally.

@eszpotanski @lpawelcz What is the motivation behind using bazel run? Why not leave this to the generated _make script?
We want bazel-orfs to be a wafer thin layer on top of ORFS and hand the job of to ORFS when we can; introduce as few new concepts as possible.
The generated _make scripts will handle many situations:

open openroad in command line(open_ targets in ORFS) or GUI mode (gui_ targets in ORFS)
create issues make issue in ORFS. Here dependencies should also be included.
Various inspections, quick local testing, like do-floorplan. This can include modifying variables or tinkering with ORFS scripts.
It will be nice to have a _docker script alongside the _make script to choose between local ORFS and the Docker version used in the project.

The main reason for using bazel run was consistency, as for Docker flow OpenROAD is run through Bazel and for local flow _make scripts are used, and right now:

using local OpenROAD - GUI/open can be executed through default _make scripts, apart from synth, where additional _open_synth_make and _gui_synth_make were created. Those two are basically the same, but were added to be more user-friendly. If you'd like to minimize number of target, e.g. _gui_synth_make can be removed and _open_synth_make script will be used for both open_ and gui_.
using OpenROAD in Docker - GUI/open can be executed with bazel run {target}_gui or bazel run {target}_open. Like other targets from Docker flow, they are run directly from Bazel, this case is similar - bazel build builds required dependencies and creates script which is executed with bazel run. It's also more natural for Bazel to use build for compilation/dependencies and run for running prepared program. Moreover, for bazel build Bazel do not share TTY with the user, so programs cannot get any input.

By removing _gui/_open targets and have only _make targets, you mean to completely abandon feature with GUI/open targets run from Docker container? Or to use _make script for running GUI/open in Docker (this would also require additional target as scripts for local and Docker flow are completely different)?
As for single _deps targets - the reason behind introducing _gui_deps and _open_deps was also to make it more user-friendly - it can be easily reduced to e.g. only _open_deps.
But creating only one _deps target for all 3 mentioned use-cases is impossible, as GUI/open for e.g. L1MetadataArray_test_floorplan requires all its dependencies and floorplan itself, where make issue requires only floorplan dependencies - so I'd propose to have one _deps for normal target and second for GUI/open targets, like:

L1MetadataArray_test_floorplan_deps
L1MetadataArray_test_floorplan_open_deps

What do you think?

@lpawelcz @eszpotanski I want to create a flow that is less Bazel oriented and more ORFS oriented.
I want to remove bazel run from the non-bazel use of ORFS. Non-bazel ORFS use is both through docker and locally installed ORFS.
We can achieve what we need with only three targets for each stage. Note that the semantics is a bit different than today:

_scripts, creates non-bazel scripts for local ORFS install and Docker. This is what the _make bazel targets do today.
make, downloads all dependencies to run the next stage, but not enough to run make open and gui_ targets. Depends on _scripts bazel target.
gui, downloads all dependencies required to run make open and gui_ targets for all stages, including synth. That synth is special is an implementation detail of _gui. Depends on _scripts bazel target. This also covers the dependencies of _make.

@oharboe, CC @eszpotanski

I want to remove bazel run from the non-bazel use of ORFS. Non-bazel ORFS use is both through docker and locally installed ORFS.

Right, so the baseline is to have scripts that can be executed straight from ./bazel-bin, just as current _make scripts.

We can achieve what we need with only three targets for each stage. Note that the semantics is a bit different than today:

_scripts, creates non-bazel scripts for local ORFS install and Docker. This is what the _make bazel targets do today.

Got it, so rename _make targets to _script. This 'family' of targets should generate 2 output files:

script for running the local flow
script for running the docker flow

_make, downloads all dependencies to run the next stage, but not enough to run make open_ and gui_ targets. Depends on _scripts bazel target.

Not sure if I understand that correctly. New _make targets should:

generate 2 scripts for running given ORFS stage (dependency on _script bazel target, generate variant for local and docker flow)
build all previous stages and all required macros
eg.: L1MetadataArray_test_floorplan_make will:

build scripts (bazel target L1MetadataArray_test_floorplan_script) capable of running ORFS make targets like: do-floorplan floorplan_gui, floorplan_open
build dependencies with docker flow:

the whole tag_array_64x184 macro,
L1MetadataArray_test stages up to synth

_gui, downloads all dependencies required to run make open_ and gui_ targets for all stages, including synth. That synth is special is an implementation detail of _gui. Depends on _scripts bazel target. This also covers the dependencies of _make.

So this one should basically only depend on _make target (_make already depends on _script) and additionally build the dependencies for running ORFS make targets *-gui/*-open
Please confirm if that is correct so we can move on with the implementation.

Comments inline:

@oharboe, CC @eszpotanski

I want to remove bazel run from the non-bazel use of ORFS. Non-bazel ORFS use is both through docker and locally installed ORFS.

Right, so the baseline is to have scripts that can be executed straight from ./bazel-bin, just as current _make scripts.

Yes.

We can achieve what we need with only three targets for each stage. Note that the semantics is a bit different than today:

_scripts, creates non-bazel scripts for local ORFS install and Docker. This is what the _make bazel targets do today.

Got it, so rename _make targets to _script. This 'family' of targets should generate 2 output files:

script for running the local flow
script for running the docker flow

and third script for running the make issue.

_make, downloads all dependencies to run the next stage, but not enough to run make open_ and gui_ targets. Depends on _scripts bazel target.

Not sure if I understand that correctly. New _make targets should:

generate 2 scripts for running given ORFS stage (dependency on _script bazel target, generate variant for local and docker flow)
build all previous stages

Only the immediately preceeding stage.

and all required macros

Yes, but not that not all stages require macros. Search for ADDITIONAL_LIB/LEFS/GDS_FILES to see what files are required for a stage.

eg.: L1MetadataArray_test_floorplan_make will:

build scripts (bazel target L1MetadataArray_test_floorplan_script) capable of running ORFS make targets like: do-floorplan floorplan_gui, floorplan_open

build dependencies with docker flow:

the whole tag_array_64x184 macro,
L1MetadataArray_test stages up to synth

Yes.
However, if you create a "place" script, then only the immediately preceeding stage, "floorplan" outputs are needed.

_gui, downloads all dependencies required to run make open_ and gui_ targets for all stages, including synth. That synth is special is an implementation detail of _gui. Depends on _scripts bazel target. This also covers the dependencies of _make.

So this one should basically only depend on _make target (_make already depends on _script) and additionally build the dependencies for running ORFS make targets *-gui/*-open

Yes.

Please confirm if that is correct so we can move on with the implementation.

With the corrections above, please proceed.
This is a bit tricky and we can't expect to get all details right on the first try, but I think we have the general direction clearly sorted out and that we can fix all the details when we have a PR to test.

OK, thanks for clarifying that out. We will now focus on the implementation according to the description above.

@lpawelcz @eszpotanski Are you waiting for me on anything for this PR?


Cannot drag-drop text at end of selection.

VSCode Version: 1.11.1
OS Version: Windows 10

Steps to Reproduce:

Select some text.
Hold Ctrl and drag the selected text.
Drop the selected text directly after the selection.
Text does not copy.

E.g. if you select the text "this is text" and Ctrl+Drag it so the cursor is just after the last "t" in "text", the text is not copied.

Dup of https://github.com/Microsoft/vscode/issues/24553 . Already fixed in Insider.


Documentation issue on page "050-tutorials/content/howto/x509_certificates/_index.md"

Can you please also describe if spec.tls field is needed after adding the label 'garden.sapcloud.io/purpose: managed-cert'
in metadata?
If spec.tls is needed, can I put a wildcard hostname like following? Also what should be the secretName value? As I am not creating the secret.
tls:
  - hosts:
    - *.ingress.<GARDENER-CLUSTER>.<GARDENER-PROJECT>.shoot.example.com
    secretName: testsecret-tls

Page: 050-tutorials/content/howto/x509_certificates/_index.md
don't remove the link to the page. It's required for the processor

@timuthy can you please provide some help to the user?

Yes, spec.tls is needed since it contains the domains for which a certificate. Furthermore, you can specify any secretName you want. A secret with that name and the certificate/key inside will be created after the issuing process.
The request for the wildcard domain looks fine, although the domain itself should be put into quotes to have a valid yaml --> "*.ingress.<GARDENER-CLUSTER>.<GARDENER-PROJECT>.shoot.example.com".
Let me update the documentation accordingly.


Best Buy 3090 FE drop on Oct 9 2pm CST not detected

Description
Best buy had a drop of 3090 FE cards around 2pm on Oct 9th that lasted ~15 min.   NVIDIA snatcher did not detect this event.
Possible solution
URL or page elements changed?

I wanted to say thank you to the developer. I managed to grab both a 3080 and a 3090 from best buy.

I wanted to say thank you to the developer. I managed to grab both a 3080 and a 3090 from best buy.

However, it only detected the 3080 like this post is stating.

I wanted to say thank you to the developer. I managed to grab both a 3080 and a 3090 from best buy.

I had the good fortune of actually being in front of my system when the alert came up at 2:00PM ET, but when I went to their website the 3080 FE cards were still all listed as "Sold Out" (I tried refreshing several times from 2:00 - 2:10 or so), and because I kept getting alerts I thought it was a bug! Might I ask if there was some "trick" you used, or perhaps the stock / availability was somehow regional? Several people on Reddit mentioned being able to add one to their cart even 15 minutes after the drop. Thanks in advance!

I had the bot running on BestBuy and it did not trigger any of the items that came back to in stock.


Improve user management documentation

The existing documentation was inaccurate and confusing.
This tries to address #121.

@nasbyj @susanmdouglas-aws @rcv-aws -- could you please review this PR?


Future proof routerExtras implementation

The fix done for #2911 is not the most future proof implementation. Whenever Angular decides to change the properties of the routerExtra the implementation might break. (As already happened during the implementation of the fix).
This issue serves to find a better approach.
@Licen-it it suggested to create new directive that extends the routerLink functionality to also add the routerExtras.
Can you describe how you see this? Is this a new directive like routerLinkExtras that should also be added on the a tag? Or do you want it to really extend the routerLink? Where would this directive live in the repo?
Thanks 🙇

@klaascuvelier just pushed the solution


Node iterator

This PR adds two major features:

Ability to iterate awaited arrays and iterables
Ability to await any element itself and "attach" the result to the underlying node ids

A few changes:

Implemented proper iterators
Activated parentNode children and made document/element IHtmlCollections all abstract so they create objects first and implement the awaited option
Changed the awaitedIterator and nodeAttachers so they don't get "create" names passed in
Constructors now specify "constructorNames" in the state. I think we should find a better way to do this in general, but I am not sure what to do quite yet (and probably not part of this PR)
HtmlCollections cause issues.. they inherit from a dom base class (HtmlCollectionBase) and that causes havoc in the structure and naming since we try to create our own HtmlCollectionBase. I have temporarily specifically called out HtmlCollections in iterators. I need your advice (and probably a future pr) to properly handle base classes

Issues I noticed:

customizer does not support chrome to change the abstract/on (it has to do with the target not having an originalTarget associated
Customizer is losing state for things like "abstract" between loads. I have to re-check querySelectorAll every time.. I didn't dive in to figure out why yet

This seems ready to merge... unless we want to quick.y fix the HTMLCollectionBase conflict.
look in files/0-imported/webidl-replacements/HTMLCollection.webidl and HTMLFormControlsCollection.webidl.
This was an override file I created to split HTMLCollection into HTMLCollection and HTMLCollectionBase. I did this because the W3C spec has HTMLFormControlsCollection inheriting from HTMLCollection then overriding the namedItem type. Typescript barfs at an child class overriding a parent type (I couldn't get it to work).
My hack was to create HTMLCollectionBase that had everything except namedItem, then allow HTMLCollection and HTMLFormControlsCollection to inherit from HTMLCollectionBase.
To solve your problem, just rename HTMLCollectionBase to something else (i.e., HTMLCollectionWithoutNamedItem).

I fixed the conflict by just renaming the internal base classes to BaseClass. Is that ok for now?


[Question] Apply Constant force

I know how to apply force, but looks like it applies once, losing momentum with time
what i want to ask is - how to apply(introduce) constant force, like gravity. for instance - lift, or thrust, or drag of flying body.
Thanks

You should use an engine event to apply it on every update.

Hopefully that answered your question so I'll close this, but feel free to comment if you still need more info.

I have a similar question where i would like to add gravity once an animated object reaches the center of the screen. Is this possible?

Sure you can use events for this, check the distance of body.position to the target point, when it gets lower than a threshold set a flag and then add forces.

Thank you! Ill be trying this today :)

I am trying to do this:
var shapeA = Bodies.rectangle(200, 00, 25, 25, {
//restitution: how bouncy an object is
restitution : .7,
render: {
sprite: {
texture: './img/purple.png'
}
}
//if statement: if body is between 134 and 318
if (Body.position >= 134 && <= 318) {
console.log("should run");
}
});

I think I might be confused as to how to check the position of the body (no if statements) and how to apply the gravity force once it is in the ideal position.
goal:
example.zip

Hey, I have a question, can u please just take a second and tell me how to use the engine event to apply constant force, for instance say , I want to apply force on a particle in electric field, so, How do I apply the force on that particle.
Thanks

Matter.Events.on(engine, 'beforeUpdate', function(event) {
//Apply force
});

This event is sent on every iteration of the simulation loop.
More at: https://brm.io/matter-js/docs/classes/Engine.html#events

How to applyForce on an circular object

https://brm.io/matter-js/docs/classes/Body.html#method_applyForce

I feel like this is a bit weird. Why do I have to iterate and set force in all my physics entities with forces applied to them before an engine update? I feel like body.force shouldn't be reset to (0,0) after a physics step.

@davidreis97 there's a plugin that makes things easier check out matter-attractors


cpp_test AsyncProgress and Events tests failing when run as part of Azure pipeline

Example: https://dev.azure.com/msft-xlang/public/_build/results?buildId=510&view=ms.vss-test-web.build-test-results-tab
I'm going to disable these tests. We will use this issue to track fixing and re-enabling them

👍

FYI, I tagged the two tests [!hide][failing] so they are excluded from a default test run, but can be manually executed by calling cpp_test.exe [failing]


When scrolled down on mobile, tapping on the Bluesky logo once should bring you to the top of the feed

Is your feature request related to a problem? Please describe.
Tapping on the Bluesky logo at the top of the feed should bring you to the top of the feed, in the same way Twitter does.
Describe alternatives you've considered

N/A
Additional context

N/A

+1 I also think this would be a useful feature. The ability to quickly return to the top of the feed by tapping the logo is an intuitive navigation pattern that many users are already familiar with.
Since this has been proposed for several months now, I'll work on implementing this feature and submit a PR with the implementation.


feat: anchored object query for workouts

Description
feat(anchored-workout-query): create a workouts query using an hkanchoredobjectquery

Adds a library method that allows to query workouts via an HKAnchoredObjectQuery, exposing a query workouts results array and a resulting base-64 encoded anchor to the react-native bridge
Adds utility methods to create an anchored query predicate with optional base-64 encoded anchor, startDate, and endDate params
Adds documentations, as well as typescript definitions
Fixes # (issue)

Type of change
Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have made corresponding changes to the documentation
[x] I have checked my code and corrected any misspellings

Hey @alfonsosn, thank you for this amazing contribution!

Hey @alfonsosn, thank you for this amazing contribution!

Happy to contribute @Macelai! I'm excited to see what you all think. AnchorQueries offer a unique advantage to SampleQueries, so hopefully this PR can serve as a blueprint for similar methods in the library.

Hey @alfonsosn!
Thank you so much for the contribution! Is super valuable and might even be a full replacer to most of our existing SampleQueries.
We are also starting a migration to Swift, which will require all of them to be re-written. We could evaluate the solution and migrate them all to the new structure (help is more than welcome 😄 )

Cool! I've done some work with Swift and HealthKit. The consensus seems to be that react-native developers really hate Objective-C haha. But my experience is that you have to write just as much code since you still need to write your RCT_Exports in objective-c. I think it just depends on the feature you're trying to achieve.

@lucaspbordignon are there any specific changes you'd like me to address on this PR?


Missing files?

Is the master branch missing a lot of files?

device.rb
compellent.rb
facts.rb
etc

The old branches contain these files, where are they in the master branch?  If they are no longer needed the installation instructions should be updated.
@gavin-scott - if there is way to get a hold of you please let me know.  I am with compellent and we are going to fork this module and move it from compcu > REST api.

@tek0011 the file structure is updated in the master branch. Now module is using "apply" model instead of "device" model. For discovery, bin/discovery.rb needs to be used.

thanks @sushilrai  - Is there better documentation somewhere, regarding the use of this module?

What is the command line argument to be used with puppet apply?

Sorry we haven’t had a chance to update the docs yet – they are way outdated. The module is definitely no longer using the puppet device module.
Here is an example manifest (with placeholder variables) we use to create a volume:
compellent::createvol{$name:
  size            => $size,
  boot            => $boot,
  volumefolder    => $volumefolder,
  purge           => $purge,
  volume_notes    => $volume_notes,
  server_notes    => $server_notes,
  replayprofile   => $replayprofile,
  storageprofile  => $storageprofile,
  servername      => $servername,
  operatingsystem => $operatingsystem,
  serverfolder    => $serverfolder,
  wwn             => $wwn,
  porttype        => $porttype,
  manual          => $manual,
  force           => $force,
  readonly        => $readonly,
  singlepath      => $singlepath,
  lun             => $lun,
  localport       => $localport
}

I’m looking more closely and it looks like the module is using some internal ASM asm-deployer code to get the host IP, username and password for the Compellent array to use:
https://github.com/dell-asm/dell-compellent/blob/485c683d0d2cf88300daa3bfb6871a00a27e5758/lib/puppet/compellent/util.rb#L7
So that won’t work outside the context of the ASM appliance. We need to change the module to use a puppet-transport resource to specify the ip/username/password. In that case your manifest would look more like:
transport { 'compellent':
  server   => '<IP_ADDRESS>',
  username => 'administrator',
  password => 'password',
}

compellent::createvol{ 'volumename':
  size            => $size,
  boot            => $boot,
  volumefolder    => $volumefolder,
  // ...
  transport => Transport['compellent']
}

We made a similar change for our dell-idrac module not too long ago to remove the internal asm-deployer dependency:
https://github.com/dell-asm/dell-idrac/pull/208
We can try to get the same change put in for the dell-compellent module but I can’t guarantee a timeline. If you have time to work on it a PR is welcome ;-)
Once these are changes are made you could create a file called manifest.pp with the appropriate code and just run puppet apply manifest.pp to execute it.

Thanks @gavin-scott !


Fix preview job deleting other previews

Yeah let's keep the issue open and can fix it with scheduling or something.


The Windows (preview) version causes Windows 11 crash with DPC_WATCHDOG_VIOLATION (133)

What is the issue?
I am running the Windows (preview) version on Windows 11 with Nvidia 4070Ti (12GB GPU memory).
The Nvidia driver is latest version 552.22, and Cuda is latest version 12.4.1. When answering some questions with relative lengthy outputs, the whole computer hang / crash with the error DPC_WATCHDOG_VIOLATION (133) . I have tried different models like deepseek-coder / wizardlm2 and encountered the same problem.
OS
Windows
GPU
Nvidia
CPU
Intel
Ollama version
0.1.32

This sounds like it may be an NVIDIA driver bug, or possibly hardware fault.  Did you get a BSOD? Did it report which driver was hung?

Yes, it got BSOD after hanging for a while. The following is the bugcheck detail. It points to nvlddmkm.sys which is nvidia display driver. I already installed the latest nvidia driver and it did not help.
`10: kd> !analyze -v

                                                                        *

                   Bugcheck Analysis                                    *

                                                                        *

DPC_WATCHDOG_VIOLATION (133)
The DPC watchdog detected a prolonged run time at an IRQL of DISPATCH_LEVEL
or above.
Arguments:
Arg1:<PHONE_NUMBER>000001, The system cumulatively spent an extended period of time at
DISPATCH_LEVEL or above.
Arg2:<PHONE_NUMBER>001e00, The watchdog period (in ticks).
Arg3: fffff80069f1c340, cast to nt!DPC_WATCHDOG_GLOBAL_TRIAGE_BLOCK, which contains
additional information regarding the cumulative timeout
Arg4:<PHONE_NUMBER>000000
Debugging Details:
BUGCHECK_CODE:  133
BUGCHECK_P1: 1
BUGCHECK_P2: 1e00
BUGCHECK_P3: fffff80069f1c340
BUGCHECK_P4: 0
FILE_IN_CAB:<PHONE_NUMBER>-01.dmp
DUMP_FILE_ATTRIBUTES: 0x1808
Kernel Generated Triage Dump
DPC_TIMEOUT_TYPE:  DPC_QUEUE_EXECUTION_TIMEOUT_EXCEEDED
BLACKBOXBSD: 1 (!blackboxbsd)
BLACKBOXNTFS: 1 (!blackboxntfs)
BLACKBOXPNP: 1 (!blackboxpnp)
BLACKBOXWINLOGON: 1
CUSTOMER_CRASH_COUNT:  1
PROCESS_NAME:  Code.exe
STACK_TEXT:
ffffd2013256b9d8 fffff800694e3739     :<PHONE_NUMBER>000133<PHONE_NUMBER>000001<PHONE_NUMBER>001e00 fffff80069f1c340 : nt!KeBugCheckEx
ffffd2013256b9e0 fffff800694e2884     : 0000be4794caa2e8 ffffd20132551180<PHONE_NUMBER>3bc48e<PHONE_NUMBER>000000 : nt!KeAccumulateTicks+0x239
ffffd2013256ba40 fffff800694e453f     :<PHONE_NUMBER>00001c<PHONE_NUMBER>001388<PHONE_NUMBER>3bc400<PHONE_NUMBER>239fd7 : nt!KiUpdateRunTime+0xf4
ffffd2013256bc00 fffff800694e08f8     :<PHONE_NUMBER>000000 ffffd2013644da00 ffffd20132551180<PHONE_NUMBER>000000 : nt!KiUpdateTime+0x63f
ffffd2013256bea0 fffff800694e01ba     : fffff80069e5fe60 ffffd2013644dab0 ffffd2013644dab0<PHONE_NUMBER>000002 : nt!KeClockInterruptNotify+0x228
ffffd2013256bf40 fffff80069467e5c     : 0000008e7f62ee25 ffffe706d81528a0 ffffe706d8152950 fffff8006961a38b : nt!HalpTimerClockInterrupt+0x10a
ffffd2013256bf70 fffff8006961a5ea     : ffffb98693716d10 ffffe706d81528a0<PHONE_NUMBER>900494<PHONE_NUMBER>000000 : nt!KiCallInterruptServiceRoutine+0x9c
ffffd2013256bfb0 fffff8006961aeb7     :<PHONE_NUMBER>90047c fffff8006961aec4<PHONE_NUMBER>900490 ffffb98693716e38 : nt!KiInterruptSubDispatchNoLockNoEtw+0xfa
ffffb98693716c90 fffff800966dd510     : fffff800966dda4a ffffe706ea9c7000 fffff80096704fde ffffe706ea9c7bf0 : nt!KiInterruptDispatchNoLockNoEtw+0x37
ffffb98693716e28 fffff800966dda4a     : ffffe706ea9c7000 fffff80096704fde ffffe706ea9c7bf0 ffffb98693716e60 : nvlddmkm+0xed510
ffffb98693716e30 ffffe706ea9c7000     : fffff80096704fde ffffe706ea9c7bf0 ffffb98693716e60 ffffe70600000000 : nvlddmkm+0xeda4a
ffffb98693716e38 fffff80096704fde     : ffffe706ea9c7bf0 ffffb98693716e60 ffffe70600000000 fffff80000000020 : 0xffffe706ea9c7000 ffffb98693716e40 ffffe706ea9c7bf0     : ffffb98693716e60 ffffe70600000000 fffff80000000020 ffffb98693716ea0 : nvlddmkm+0x114fde ffffb98693716e48 ffffb98693716e60     : ffffe70600000000 fffff80000000020 ffffb98693716ea0<PHONE_NUMBER>000000 : 0xffffe706ea9c7bf0
ffffb98693716e50 ffffe70600000000     : fffff80000000020 ffffb98693716ea0<PHONE_NUMBER>000000<PHONE_NUMBER>000000 : 0xffffb98693716e60 ffffb98693716e58 fffff80000000020     : ffffb98693716ea0<PHONE_NUMBER>000000<PHONE_NUMBER>000000<PHONE_NUMBER>900494 : 0xffffe70600000000
ffffb98693716e60 ffffb98693716ea0     :<PHONE_NUMBER>000000<PHONE_NUMBER>000000<PHONE_NUMBER>900494<PHONE_NUMBER>000000 : 0xfffff80000000020 ffffb98693716e68<PHONE_NUMBER>000000     :<PHONE_NUMBER>000000<PHONE_NUMBER>900494<PHONE_NUMBER>000000<PHONE_NUMBER>000000 : 0xffffb98693716ea0
SYMBOL_NAME:  nvlddmkm+ed510
MODULE_NAME: nvlddmkm
IMAGE_NAME:  nvlddmkm.sys`

Which driver version is installed on your system? How much system RAM do you have? How big is the model you've been loading in to ollama?

@binxie33 our current theory is you ran low on system memory trying to load a large model, possibly with VRAM paging taking place on the GPU.  If you can repro this failure, can you run nvidia-smi to see if the GPU's VRAM is ~full, and systeminfo | find "Virtual Memory" may also help shed some light on what's going on.  We'd also like to understand how much physical RAM you have in the system.

If you're still having problems, please share the information above and I'll re-open.


Lack of APNS documentation and probable apns alert issue

Lack of apns documentation. Had to read the codebase. Anyway get an error trying to send an alert via APNS.
message = {
  apns: { payload: { alert: { title: "title" }, badge: 2 } },
  token: "my_fcm_reg_id"
}

FirebaseCloudMessenger.send(message: message)

=> FirebaseCloudMessenger::BadRequest:       Status: 400

      Request contains an invalid argument.

as well as
notification = FirebaseCloudMessenger::Notification.new(title: "title")
apns_alert = FirebaseCloudMessenger::Apns::Alert.new(title: "title")
apns_payload = FirebaseCloudMessenger::Apns::Payload.new(alert: apns_alert, badge: 2)
apns_config = FirebaseCloudMessenger::Apns::Config.new(payload: apns_payload)

msg = FirebaseCloudMessenger::Message.new(name: "name",
                                          notification: notification,
                                          apns: apns_config,
                                          token: "my_fcm_reg_id")

       =>
FirebaseCloudMessenger::BadRequest:       Status: 400

      Request contains an invalid argument.

Correct me if I'm trying to send it the wrong way.

Thanks for opening the issue! Running validations against the FCM api gives us a hint about what went wrong:
In the first case, let's instantiate a FirebaseCloudMessenger::Message with your message hash and run some validations against the FCM api to see what's going on:
[26] pry(main)> m = FirebaseCloudMessenger::Message.new(message)
=> #<FirebaseCloudMessenger::Message:0x007fe78080a268>
[27] pry(main)> m.valid?(against_api: true)
=> false
[28] pry(main)> m.errors
=><EMAIL_ADDRESS>"fieldViolations"=>[{"field"=>"message.apns.payload", "description"=>"Payload of Apple Push Notification Service must contain an [aps] key."}]},
<EMAIL_ADDRESS>"errorCode"=>"INVALID_ARGUMENT"}]

So the problem is that the message should look like this:
message = {
  apns: {
    payload: {
      aps: {
        alert: {
          title: "title"
        },
        badge: 2 }
    }
  },
  token: "my_fcm_reg_id"
}

I'm assuming it's the same problem in the second case. The reason you forgot the aps key is because you correctly read my incorrect code. 😢 FirebaseCloudMessenger::Apns::Payload will need to be modified, as well as the json schema.
In the meantime, modifying your first example by sending the message hash above will work, since it will bypass the buggy Payload class.  Those data classes are meant to just be helpful, but are not really necessary at the end of the day.
As for documentation, I was relying on Google's own docs (https://firebase.google.com/docs/reference/fcm/rest/v1/projects.messages#Message) to be clear, but I agree that's not ideal. I think it would be great to start a wiki for this project with a bunch of different examples, including for APNS.
Let me know if you'd like to contribute a patch or some docs. Otherwise, I should be able to devote some time to it this weekend or next week.


[jvm-packages] xgboost4j-spark built against Scala 2.12 hangs during training on Windows 10

This is an issue with regards xgboost4j-spark hanging when training a model on Windows, when built from source against Scala 2.12.4.
Environment

XGBoost4j and XGBoost4j-spark 0.90
Windows 10, 64 bit, Home
Python 3.6.3
Scala 2.12.4
Java 8
CMake 3.15.4
Windows 8.1 SDK (via Visual Studio Community Edition 2015)

Steps to reproduce
First I built the jars, following the instructions here (https://xgboost.readthedocs.io/en/latest/jvm/), after which I can import the resulting jars into my project as unmanaged jars or install them into my local Maven repo. Note I had to make one change to create_jni.py, since my Python installation directory had spaces in it, so I worked around this by replacing sys.executable -> "C:\Progra~1\Python36\python.exe".
Next I run the simple example code below, just to put XGBoost4j-spark through its paces:
import ml.dmlc.xgboost4j.scala.spark.{TrackerConf, XGBoostClassifier}
import org.apache.spark.ml.feature.{StringIndexer, VectorAssembler}
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.types.{DoubleType, StringType, StructField, StructType}

object SimpleXGBoost extends App {

  val spark = SparkSession
    .builder()
    .appName("SimpleXGBoost Application")
    .master("local[1]")
    .getOrCreate()

  spark.sparkContext.setLogLevel("INFO")

  val schema = new StructType(Array(
    StructField("sepal length", DoubleType, true),
    StructField("sepal width", DoubleType, true),
    StructField("petal length", DoubleType, true),
    StructField("petal width", DoubleType, true),
    StructField("class", StringType, true)))
  val rawInput = spark.read.schema(schema).csv("C:/Data/iris.data.csv")

  rawInput.show(10)

  val stringIndexer = new StringIndexer().
    setInputCol("class").
    setOutputCol("classIndex").
    fit(rawInput)
  val labelTransformed = stringIndexer.transform(rawInput).drop("class")

  val vectorAssembler = new VectorAssembler().
    setInputCols(Array("sepal length", "sepal width", "petal length", "petal width")).
    setOutputCol("features")
  val xgbInput = vectorAssembler.transform(labelTransformed).select("features", "classIndex")
  val tracker_conf = new TrackerConf(20 * 1000, "scala")
  val xgbParam = Map("eta" -> 0.1f,
    "objective" -> "multi:softprob",
    "num_class" -> 3,
    "num_round" -> 10,
    "num_workers" -> 1,
    "nthread" -> 1,
    "tracker_conf" -> tracker_conf,
    "verbosity" -> 3)
  val xgbClassifier = new XGBoostClassifier(xgbParam).
    setFeaturesCol("features").
    setLabelCol("classIndex")

  val xgbClassificationModel = xgbClassifier.fit(xgbInput)

  spark.stop()
}

On running this code, everything is fine until it reaches the xgbClassifier.fit(xgbInput), this is where things hang until the Scala tracker times out. This produces the following stack trace:
2019-11-09 21:51:33,567 |  INFO |              Logging |   54 | Running Spark version 2.4.0
2019-11-09 21:51:33,822 |  WARN |     NativeCodeLoader |   62 | Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2019-11-09 21:51:33,922 |  INFO |              Logging |   54 | Submitted application: SimpleXGBoost Application
2019-11-09 21:51:34,007 |  INFO |              Logging |   54 | Changing view acls to: simon
2019-11-09 21:51:34,007 |  INFO |              Logging |   54 | Changing modify acls to: simon
2019-11-09 21:51:34,008 |  INFO |              Logging |   54 | Changing view acls groups to:
2019-11-09 21:51:34,009 |  INFO |              Logging |   54 | Changing modify acls groups to:
2019-11-09 21:51:34,009 |  INFO |              Logging |   54 | SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(simon); groups with view permissions: Set(); users  with modify permissions: Set(simon); groups with modify permissions: Set()
2019-11-09 21:51:35,097 |  INFO |              Logging |   54 | Successfully started service 'sparkDriver' on port 61123.
2019-11-09 21:51:35,121 |  INFO |              Logging |   54 | Registering MapOutputTracker
2019-11-09 21:51:35,145 |  INFO |              Logging |   54 | Registering BlockManagerMaster
2019-11-09 21:51:35,147 |  INFO |              Logging |   54 | Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
2019-11-09 21:51:35,148 |  INFO |              Logging |   54 | BlockManagerMasterEndpoint up
2019-11-09 21:51:35,160 |  INFO |              Logging |   54 | Created local directory at C:\Users\simon\AppData\Local\Temp\blockmgr-2cfe480c-59d8-4167-8cce-3e31a33fad90
2019-11-09 21:51:35,189 |  INFO |              Logging |   54 | MemoryStore started with capacity 4.1 GB
2019-11-09 21:51:35,206 |  INFO |              Logging |   54 | Registering OutputCommitCoordinator
2019-11-09 21:51:35,296 |  INFO |                  Log |  192 | Logging initialized @7614ms
2019-11-09 21:51:35,365 |  INFO |               Server |  351 | jetty-9.3.z-SNAPSHOT, build timestamp: unknown, git hash: unknown
2019-11-09 21:51:35,380 |  INFO |               Server |  419 | Started @7698ms
2019-11-09 21:51:35,406 |  INFO |    AbstractConnector |  278 | Started ServerConnector@6d0b5baf{HTTP/1.1,[http/1.1]}{<IP_ADDRESS>:4040}
2019-11-09 21:51:35,407 |  INFO |              Logging |   54 | Successfully started service 'SparkUI' on port 4040.
2019-11-09 21:51:35,428 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@76ba13c{/jobs,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,429 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@44c79f32{/jobs/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,429 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@7fcbe147{/jobs/job,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,430 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@743cb8e0{/jobs/job/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,431 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@c7a975a{/stages,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,431 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@2c1b9e4b{/stages/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,432 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@757d6814{/stages/stage,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,432 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@4c168660{/stages/stage/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,433 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@52b56a3e{/stages/pool,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,434 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@fd0e5b6{/stages/pool/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,434 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@4eed46ee{/storage,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,435 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@36b0fcd5{/storage/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,435 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@4fad94a7{/storage/rdd,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,436 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@475835b1{/storage/rdd/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,436 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@6326d182{/environment,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,437 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@5241cf67{/environment/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,438 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@716a7124{/executors,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,438 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@77192705{/executors/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,439 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@226642a5{/executors/threadDump,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,439 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@7e809b79{/executors/threadDump/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,445 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@5cc126dc{/static,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,446 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@64337702{/,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,447 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@2cf92cc7{/api,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,447 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@611df6e3{/jobs/job/kill,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,448 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@5f2f577{/stages/stage/kill,null,AVAILABLE,@Spark}
2019-11-09 21:51:35,449 |  INFO |              Logging |   54 | Bound SparkUI to <IP_ADDRESS>, and started at http://DESKTOP-4869294:4040
2019-11-09 21:51:35,576 |  INFO |              Logging |   54 | Starting executor ID driver on host localhost
2019-11-09 21:51:35,644 |  INFO |              Logging |   54 | Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 61136.
2019-11-09 21:51:35,645 |  INFO |              Logging |   54 | Server created on DESKTOP-4869294:61136
2019-11-09 21:51:35,646 |  INFO |              Logging |   54 | Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
2019-11-09 21:51:35,675 |  INFO |              Logging |   54 | Registering BlockManager BlockManagerId(driver, DESKTOP-4869294, 61136, None)
2019-11-09 21:51:35,680 |  INFO |              Logging |   54 | Registering block manager DESKTOP-4869294:61136 with 4.1 GB RAM, BlockManagerId(driver, DESKTOP-4869294, 61136, None)
2019-11-09 21:51:35,683 |  INFO |              Logging |   54 | Registered BlockManager BlockManagerId(driver, DESKTOP-4869294, 61136, None)
2019-11-09 21:51:35,684 |  INFO |              Logging |   54 | Initialized BlockManager: BlockManagerId(driver, DESKTOP-4869294, 61136, None)
2019-11-09 21:51:35,840 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@46b695ec{/metrics/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:36,016 |  INFO |              Logging |   54 | Setting hive.metastore.warehouse.dir ('null') to the value of spark.sql.warehouse.dir ('file:/C:/GIT/blue-moon/spark-warehouse').
2019-11-09 21:51:36,017 |  INFO |              Logging |   54 | Warehouse path is 'file:/C:/GIT/blue-moon/spark-warehouse'.
2019-11-09 21:51:36,027 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@712ca57b{/SQL,null,AVAILABLE,@Spark}
2019-11-09 21:51:36,027 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@4564e94b{/SQL/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:36,028 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@27abb83e{/SQL/execution,null,AVAILABLE,@Spark}
2019-11-09 21:51:36,029 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@69e308c6{/SQL/execution/json,null,AVAILABLE,@Spark}
2019-11-09 21:51:36,030 |  INFO |       ContextHandler |  781 | Started o.s.j.s.ServletContextHandler@1efdcd5{/static/sql,null,AVAILABLE,@Spark}
2019-11-09 21:51:36,662 |  INFO |              Logging |   54 | Registered StateStoreCoordinator endpoint
2019-11-09 21:51:38,579 |  INFO |              Logging |   54 | Pruning directories with:
2019-11-09 21:51:38,584 |  INFO |              Logging |   54 | Post-Scan Filters:
2019-11-09 21:51:38,587 |  INFO |              Logging |   54 | Output Data Schema: struct<sepal length: double, sepal width: double, petal length: double, petal width: double, class: string ... 3 more fields>
2019-11-09 21:51:38,593 |  INFO |              Logging |   54 | Pushed Filters:
2019-11-09 21:51:38,985 |  INFO |              Logging |   54 | Code generated in 203.6344 ms
2019-11-09 21:51:39,221 |  INFO |              Logging |   54 | Code generated in 28.7679 ms
2019-11-09 21:51:39,309 |  INFO |              Logging |   54 | Block broadcast_0 stored as values in memory (estimated size 220.3 KB, free 4.1 GB)
2019-11-09 21:51:40,436 |  INFO |              Logging |   54 | Block broadcast_0_piece0 stored as bytes in memory (estimated size 20.6 KB, free 4.1 GB)
2019-11-09 21:51:40,439 |  INFO |              Logging |   54 | Added broadcast_0_piece0 in memory on DESKTOP-4869294:61136 (size: 20.6 KB, free: 4.1 GB)
2019-11-09 21:51:40,441 |  INFO |              Logging |   54 | Created broadcast 0 from show at SimpleXGBoost.scala:24
2019-11-09 21:51:40,470 |  INFO |              Logging |   54 | Planning scan with bin packing, max size: 4198855 bytes, open cost is considered as scanning 4194304 bytes.
2019-11-09 21:51:40,599 |  INFO |              Logging |   54 | Starting job: show at SimpleXGBoost.scala:24
2019-11-09 21:51:40,622 |  INFO |              Logging |   54 | Got job 0 (show at SimpleXGBoost.scala:24) with 1 output partitions
2019-11-09 21:51:40,623 |  INFO |              Logging |   54 | Final stage: ResultStage 0 (show at SimpleXGBoost.scala:24)
2019-11-09 21:51:40,623 |  INFO |              Logging |   54 | Parents of final stage: List()
2019-11-09 21:51:40,624 |  INFO |              Logging |   54 | Missing parents: List()
2019-11-09 21:51:40,628 |  INFO |              Logging |   54 | Submitting ResultStage 0 (MapPartitionsRDD[3] at show at SimpleXGBoost.scala:24), which has no missing parents
2019-11-09 21:51:40,728 |  INFO |              Logging |   54 | Block broadcast_1 stored as values in memory (estimated size 15.1 KB, free 4.1 GB)
2019-11-09 21:51:40,730 |  INFO |              Logging |   54 | Block broadcast_1_piece0 stored as bytes in memory (estimated size 7.8 KB, free 4.1 GB)
2019-11-09 21:51:40,731 |  INFO |              Logging |   54 | Added broadcast_1_piece0 in memory on DESKTOP-4869294:61136 (size: 7.8 KB, free: 4.1 GB)
2019-11-09 21:51:40,732 |  INFO |              Logging |   54 | Created broadcast 1 from broadcast at DAGScheduler.scala:1161
2019-11-09 21:51:40,747 |  INFO |              Logging |   54 | Submitting 1 missing tasks from ResultStage 0 (MapPartitionsRDD[3] at show at SimpleXGBoost.scala:24) (first 15 tasks are for partitions Vector(0))
2019-11-09 21:51:40,748 |  INFO |              Logging |   54 | Adding task set 0.0 with 1 tasks
2019-11-09 21:51:40,809 |  INFO |              Logging |   54 | Starting task 0.0 in stage 0.0 (TID 0, localhost, executor driver, partition 0, PROCESS_LOCAL, 7786 bytes)
2019-11-09 21:51:40,819 |  INFO |              Logging |   54 | Running task 0.0 in stage 0.0 (TID 0)
2019-11-09 21:51:41,117 |  INFO |              Logging |   54 | Reading File path: file:///C:/Data/iris.data.csv, range: 0-4551, partition values: [empty row]
2019-11-09 21:51:41,135 |  INFO |              Logging |   54 | Code generated in 11.3314 ms
2019-11-09 21:51:41,201 |  INFO |              Logging |   54 | Finished task 0.0 in stage 0.0 (TID 0). 1378 bytes result sent to driver
2019-11-09 21:51:41,209 |  INFO |              Logging |   54 | Finished task 0.0 in stage 0.0 (TID 0) in 420 ms on localhost (executor driver) (1/1)
2019-11-09 21:51:41,211 |  INFO |              Logging |   54 | Removed TaskSet 0.0, whose tasks have all completed, from pool
2019-11-09 21:51:41,217 |  INFO |              Logging |   54 | ResultStage 0 (show at SimpleXGBoost.scala:24) finished in 0.575 s
2019-11-09 21:51:41,221 |  INFO |              Logging |   54 | Job 0 finished: show at SimpleXGBoost.scala:24, took 0.621541 s
+------------+-----------+------------+-----------+-----------+
|sepal length|sepal width|petal length|petal width|      class|
+------------+-----------+------------+-----------+-----------+
|         5.1|        3.5|         1.4|        0.2|Iris-setosa|
|         4.9|        3.0|         1.4|        0.2|Iris-setosa|
|         4.7|        3.2|         1.3|        0.2|Iris-setosa|
|         4.6|        3.1|         1.5|        0.2|Iris-setosa|
|         5.0|        3.6|         1.4|        0.2|Iris-setosa|
|         5.4|        3.9|         1.7|        0.4|Iris-setosa|
|         4.6|        3.4|         1.4|        0.3|Iris-setosa|
|         5.0|        3.4|         1.5|        0.2|Iris-setosa|
|         4.4|        2.9|         1.4|        0.2|Iris-setosa|
|         4.9|        3.1|         1.5|        0.1|Iris-setosa|
+------------+-----------+------------+-----------+-----------+
only showing top 10 rows

2019-11-09 21:51:41,350 |  INFO |              Logging |   54 | Pruning directories with:
2019-11-09 21:51:41,351 |  INFO |              Logging |   54 | Post-Scan Filters: AtLeastNNulls(n, class#4)
2019-11-09 21:51:41,352 |  INFO |              Logging |   54 | Output Data Schema: struct<class: string>
2019-11-09 21:51:41,354 |  INFO |              Logging |   54 | Pushed Filters:
2019-11-09 21:51:41,380 |  INFO |              Logging |   54 | Code generated in 12.924 ms
2019-11-09 21:51:41,406 |  INFO |              Logging |   54 | Block broadcast_2 stored as values in memory (estimated size 220.3 KB, free 4.1 GB)
2019-11-09 21:51:41,420 |  INFO |              Logging |   54 | Block broadcast_2_piece0 stored as bytes in memory (estimated size 20.6 KB, free 4.1 GB)
2019-11-09 21:51:41,422 |  INFO |              Logging |   54 | Added broadcast_2_piece0 in memory on DESKTOP-4869294:61136 (size: 20.6 KB, free: 4.1 GB)
2019-11-09 21:51:41,424 |  INFO |              Logging |   54 | Created broadcast 2 from rdd at StringIndexer.scala:137
2019-11-09 21:51:41,425 |  INFO |              Logging |   54 | Planning scan with bin packing, max size: 4198855 bytes, open cost is considered as scanning 4194304 bytes.
2019-11-09 21:51:41,516 |  INFO |              Logging |   54 | Starting job: countByValue at StringIndexer.scala:140
2019-11-09 21:51:41,793 |  INFO |              Logging |   54 | Registering RDD 10 (countByValue at StringIndexer.scala:140)
2019-11-09 21:51:41,796 |  INFO |              Logging |   54 | Got job 1 (countByValue at StringIndexer.scala:140) with 1 output partitions
2019-11-09 21:51:41,796 |  INFO |              Logging |   54 | Final stage: ResultStage 2 (countByValue at StringIndexer.scala:140)
2019-11-09 21:51:41,796 |  INFO |              Logging |   54 | Parents of final stage: List(ShuffleMapStage 1)
2019-11-09 21:51:41,798 |  INFO |              Logging |   54 | Missing parents: List(ShuffleMapStage 1)
2019-11-09 21:51:41,799 |  INFO |              Logging |   54 | Submitting ShuffleMapStage 1 (MapPartitionsRDD[10] at countByValue at StringIndexer.scala:140), which has no missing parents
2019-11-09 21:51:41,826 |  INFO |              Logging |   54 | Block broadcast_3 stored as values in memory (estimated size 19.3 KB, free 4.1 GB)
2019-11-09 21:51:41,856 |  INFO |              Logging |   54 | Block broadcast_3_piece0 stored as bytes in memory (estimated size 10.3 KB, free 4.1 GB)
2019-11-09 21:51:41,856 |  INFO |              Logging |   54 | Added broadcast_3_piece0 in memory on DESKTOP-4869294:61136 (size: 10.3 KB, free: 4.1 GB)
2019-11-09 21:51:41,857 |  INFO |              Logging |   54 | Created broadcast 3 from broadcast at DAGScheduler.scala:1161
2019-11-09 21:51:41,860 |  INFO |              Logging |   54 | Submitting 1 missing tasks from ShuffleMapStage 1 (MapPartitionsRDD[10] at countByValue at StringIndexer.scala:140) (first 15 tasks are for partitions Vector(0))
2019-11-09 21:51:41,860 |  INFO |              Logging |   54 | Adding task set 1.0 with 1 tasks
2019-11-09 21:51:41,863 |  INFO |              Logging |   54 | Starting task 0.0 in stage 1.0 (TID 1, localhost, executor driver, partition 0, PROCESS_LOCAL, 7775 bytes)
2019-11-09 21:51:41,863 |  INFO |              Logging |   54 | Running task 0.0 in stage 1.0 (TID 1)
2019-11-09 21:51:41,948 |  INFO |              Logging |   54 | Removed broadcast_0_piece0 on DESKTOP-4869294:61136 in memory (size: 20.6 KB, free: 4.1 GB)
2019-11-09 21:51:41,954 |  INFO |              Logging |   54 | Cleaned accumulator 20
2019-11-09 21:51:41,954 |  INFO |              Logging |   54 | Cleaned accumulator 16
2019-11-09 21:51:41,954 |  INFO |              Logging |   54 | Cleaned accumulator 22
2019-11-09 21:51:41,954 |  INFO |              Logging |   54 | Cleaned accumulator 12
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 28
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 10
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 29
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 14
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 21
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 4
2019-11-09 21:51:41,955 |  INFO |              Logging |   54 | Cleaned accumulator 11
2019-11-09 21:51:41,957 |  INFO |              Logging |   54 | Removed broadcast_1_piece0 on DESKTOP-4869294:61136 in memory (size: 7.8 KB, free: 4.1 GB)
2019-11-09 21:51:41,959 |  INFO |              Logging |   54 | Cleaned accumulator 18
2019-11-09 21:51:41,959 |  INFO |              Logging |   54 | Cleaned accumulator 5
2019-11-09 21:51:41,959 |  INFO |              Logging |   54 | Cleaned accumulator 17
2019-11-09 21:51:41,959 |  INFO |              Logging |   54 | Cleaned accumulator 26
2019-11-09 21:51:41,959 |  INFO |              Logging |   54 | Cleaned accumulator 9
2019-11-09 21:51:41,959 |  INFO |              Logging |   54 | Cleaned accumulator 25
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 1
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 7
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 6
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 13
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 8
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 27
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 24
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 15
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 19
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 3
2019-11-09 21:51:41,960 |  INFO |              Logging |   54 | Cleaned accumulator 0
2019-11-09 21:51:41,961 |  INFO |              Logging |   54 | Cleaned accumulator 2
2019-11-09 21:51:41,961 |  INFO |              Logging |   54 | Cleaned accumulator 23
2019-11-09 21:51:41,984 |  INFO |              Logging |   54 | Code generated in 8.0033 ms
2019-11-09 21:51:42,010 |  INFO |              Logging |   54 | Reading File path: file:///C:/Data/iris.data.csv, range: 0-4551, partition values: [empty row]
2019-11-09 21:51:42,018 |  INFO |              Logging |   54 | Code generated in 6.4778 ms
2019-11-09 21:51:42,066 |  INFO |              Logging |   54 | Finished task 0.0 in stage 1.0 (TID 1). 1828 bytes result sent to driver
2019-11-09 21:51:42,068 |  INFO |              Logging |   54 | Finished task 0.0 in stage 1.0 (TID 1) in 206 ms on localhost (executor driver) (1/1)
2019-11-09 21:51:42,069 |  INFO |              Logging |   54 | Removed TaskSet 1.0, whose tasks have all completed, from pool
2019-11-09 21:51:42,070 |  INFO |              Logging |   54 | ShuffleMapStage 1 (countByValue at StringIndexer.scala:140) finished in 0.267 s
2019-11-09 21:51:42,070 |  INFO |              Logging |   54 | looking for newly runnable stages
2019-11-09 21:51:42,071 |  INFO |              Logging |   54 | running: Set()
2019-11-09 21:51:42,071 |  INFO |              Logging |   54 | waiting: Set(ResultStage 2)
2019-11-09 21:51:42,071 |  INFO |              Logging |   54 | failed: Set()
2019-11-09 21:51:42,076 |  INFO |              Logging |   54 | Submitting ResultStage 2 (ShuffledRDD[11] at countByValue at StringIndexer.scala:140), which has no missing parents
2019-11-09 21:51:42,082 |  INFO |              Logging |   54 | Block broadcast_4 stored as values in memory (estimated size 3.9 KB, free 4.1 GB)
2019-11-09 21:51:42,084 |  INFO |              Logging |   54 | Block broadcast_4_piece0 stored as bytes in memory (estimated size 2.4 KB, free 4.1 GB)
2019-11-09 21:51:42,086 |  INFO |              Logging |   54 | Added broadcast_4_piece0 in memory on DESKTOP-4869294:61136 (size: 2.4 KB, free: 4.1 GB)
2019-11-09 21:51:42,086 |  INFO |              Logging |   54 | Created broadcast 4 from broadcast at DAGScheduler.scala:1161
2019-11-09 21:51:42,087 |  INFO |              Logging |   54 | Submitting 1 missing tasks from ResultStage 2 (ShuffledRDD[11] at countByValue at StringIndexer.scala:140) (first 15 tasks are for partitions Vector(0))
2019-11-09 21:51:42,087 |  INFO |              Logging |   54 | Adding task set 2.0 with 1 tasks
2019-11-09 21:51:42,093 |  INFO |              Logging |   54 | Starting task 0.0 in stage 2.0 (TID 2, localhost, executor driver, partition 0, ANY, 7141 bytes)
2019-11-09 21:51:42,093 |  INFO |              Logging |   54 | Running task 0.0 in stage 2.0 (TID 2)
2019-11-09 21:51:42,110 |  INFO |              Logging |   54 | Getting 1 non-empty blocks including 1 local blocks and 0 remote blocks
2019-11-09 21:51:42,111 |  INFO |              Logging |   54 | Started 0 remote fetches in 3 ms
2019-11-09 21:51:42,141 |  INFO |              Logging |   54 | Finished task 0.0 in stage 2.0 (TID 2). 1314 bytes result sent to driver
2019-11-09 21:51:42,143 |  INFO |              Logging |   54 | Finished task 0.0 in stage 2.0 (TID 2) in 51 ms on localhost (executor driver) (1/1)
2019-11-09 21:51:42,143 |  INFO |              Logging |   54 | Removed TaskSet 2.0, whose tasks have all completed, from pool
2019-11-09 21:51:42,144 |  INFO |              Logging |   54 | ResultStage 2 (countByValue at StringIndexer.scala:140) finished in 0.063 s
2019-11-09 21:51:42,144 |  INFO |              Logging |   54 | Job 1 finished: countByValue at StringIndexer.scala:140, took 0.628652 s
2019-11-09 21:51:42,521 |  INFO |              Logging |   54 | Pruning directories with:
2019-11-09 21:51:42,522 |  INFO |              Logging |   54 | Post-Scan Filters:
2019-11-09 21:51:42,522 |  INFO |              Logging |   54 | Output Data Schema: struct<sepal length: double, sepal width: double, petal length: double, petal width: double, class: string ... 3 more fields>
2019-11-09 21:51:42,522 |  INFO |              Logging |   54 | Pushed Filters:
2019-11-09 21:51:42,571 |  INFO |              Logging |   54 | Code generated in 28.7664 ms
2019-11-09 21:51:42,591 |  INFO |              Logging |   54 | Block broadcast_5 stored as values in memory (estimated size 220.3 KB, free 4.1 GB)
2019-11-09 21:51:42,602 |  INFO |              Logging |   54 | Block broadcast_5_piece0 stored as bytes in memory (estimated size 20.6 KB, free 4.1 GB)
2019-11-09 21:51:42,603 |  INFO |              Logging |   54 | Added broadcast_5_piece0 in memory on DESKTOP-4869294:61136 (size: 20.6 KB, free: 4.1 GB)
2019-11-09 21:51:42,604 |  INFO |              Logging |   54 | Created broadcast 5 from rdd at DataUtils.scala:162
2019-11-09 21:51:42,605 |  INFO |              Logging |   54 | Planning scan with bin packing, max size: 4198855 bytes, open cost is considered as scanning 4194304 bytes.
2019-11-09 21:51:42,643 |  INFO |             XGBoost$ |  492 | Running XGBoost 1.0.0-SNAPSHOT with parameters:
alpha -> 0.0
min_child_weight -> 1.0
sample_type -> uniform
base_score -> 0.5
colsample_bylevel -> 1.0
grow_policy -> depthwise
skip_drop -> 0.0
lambda_bias -> 0.0
silent -> 0
scale_pos_weight -> 1.0
seed -> 0
cache_training_set -> false
features_col -> features
num_early_stopping_rounds -> 0
label_col -> classIndex
num_workers -> 1
subsample -> 1.0
lambda -> 1.0
max_depth -> 6
probability_col -> probability
raw_prediction_col -> rawPrediction
tree_limit -> 0
num_class -> 3
custom_eval -> null
rate_drop -> 0.0
max_bin -> 16
train_test_ratio -> 1.0
use_external_memory -> false
objective -> multi:softprob
eval_metric -> merror
num_round -> 10
timeout_request_workers -> 1800000
missing -> NaN
checkpoint_path ->
tracker_conf -> TrackerConf(20000,scala)
tree_method -> auto
max_delta_step -> 0.0
eta -> 0.1
verbosity -> 3
colsample_bytree -> 1.0
normalize_type -> tree
custom_obj -> null
gamma -> 0.0
sketch_eps -> 0.03
nthread -> 1
prediction_col -> prediction
checkpoint_interval -> -1
2019-11-09 21:51:42,650 |  WARN | ecutionParamsFactory |  175 | train_test_ratio is deprecated since XGBoost 0.82, we recommend to explicitly pass a training and multiple evaluation datasets by passing 'eval_sets' and 'eval_set_names'
2019-11-09 21:51:42,948 |  INFO |              Logging |   54 | Cleaned accumulator 54
2019-11-09 21:51:42,950 |  INFO |              Logging |   54 | Cleaned accumulator 68
2019-11-09 21:51:42,950 |  INFO |              Logging |   54 | Cleaned accumulator 34
2019-11-09 21:51:42,950 |  INFO |              Logging |   54 | Cleaned accumulator 76
2019-11-09 21:51:42,950 |  INFO |              Logging |   54 | Cleaned accumulator 51
2019-11-09 21:51:42,951 |  INFO |              Logging |   54 | Cleaned accumulator 64
2019-11-09 21:51:42,951 |  INFO |              Logging |   54 | Cleaned accumulator 46
2019-11-09 21:51:42,951 |  INFO |              Logging |   54 | Cleaned accumulator 74
2019-11-09 21:51:42,951 |  INFO |              Logging |   54 | Cleaned accumulator 77
2019-11-09 21:51:42,951 |  INFO |              Logging |   54 | Cleaned accumulator 30
2019-11-09 21:51:42,952 |  INFO |              Logging |   54 | Removed broadcast_3_piece0 on DESKTOP-4869294:61136 in memory (size: 10.3 KB, free: 4.1 GB)
2019-11-09 21:51:42,954 |  INFO |              Logging |   54 | Cleaned accumulator 37
2019-11-09 21:51:42,955 |  INFO |              Logging |   54 | Cleaned accumulator 70
2019-11-09 21:51:42,958 |  INFO |              Logging |   54 | Cleaned shuffle 0
2019-11-09 21:51:42,958 |  INFO |              Logging |   54 | Cleaned accumulator 55
2019-11-09 21:51:42,958 |  INFO |              Logging |   54 | Cleaned accumulator 67
2019-11-09 21:51:42,958 |  INFO |              Logging |   54 | Cleaned accumulator 43
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 33
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 72
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 31
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 42
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 75
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 81
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 48
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 40
2019-11-09 21:51:42,959 |  INFO |              Logging |   54 | Cleaned accumulator 36
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 47
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 49
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 73
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 32
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 41
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 58
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 84
2019-11-09 21:51:42,960 |  INFO |              Logging |   54 | Cleaned accumulator 45
2019-11-09 21:51:42,961 |  INFO |              Logging |   54 | Cleaned accumulator 52
2019-11-09 21:51:42,962 |  INFO |              Logging |   54 | Removed broadcast_2_piece0 on DESKTOP-4869294:61136 in memory (size: 20.6 KB, free: 4.1 GB)
2019-11-09 21:51:42,963 |  INFO |              Logging |   54 | Cleaned accumulator 39
2019-11-09 21:51:42,963 |  INFO |              Logging |   54 | Cleaned accumulator 56
2019-11-09 21:51:42,963 |  INFO |              Logging |   54 | Cleaned accumulator 85
2019-11-09 21:51:42,963 |  INFO |              Logging |   54 | Cleaned accumulator 60
2019-11-09 21:51:42,963 |  INFO |              Logging |   54 | Cleaned accumulator 80
2019-11-09 21:51:42,963 |  INFO |              Logging |   54 | Cleaned accumulator 62
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 35
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 61
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 69
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 79
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 63
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 83
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 38
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 57
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 59
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 65
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 71
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 78
2019-11-09 21:51:42,964 |  INFO |              Logging |   54 | Cleaned accumulator 82
2019-11-09 21:51:42,965 |  INFO |              Logging |   54 | Cleaned accumulator 50
2019-11-09 21:51:42,965 |  INFO |              Logging |   54 | Cleaned accumulator 66
2019-11-09 21:51:42,965 |  INFO |              Logging |   54 | Cleaned accumulator 53
2019-11-09 21:51:42,966 |  INFO |              Logging |   54 | Removed broadcast_4_piece0 on DESKTOP-4869294:61136 in memory (size: 2.4 KB, free: 4.1 GB)
2019-11-09 21:51:42,967 |  INFO |              Logging |   54 | Cleaned accumulator 44
[INFO] [11/09/2019 21:06:26.730] [RabitTracker-akka.actor.default-dispatcher-6] [akka://RabitTracker/user/Handler] Tracker listening @ <IP_ADDRESS>:51236
[INFO] [11/09/2019 21:06:26.731] [RabitTracker-akka.actor.default-dispatcher-6] [akka://RabitTracker/user/Handler] Worker connection timeout is 20 seconds.
2019-11-09 21:06:26,746 |  INFO | rkParallelismTracker |   84 | starting training with timeout set as 1800000 ms for waiting for resources
2019-11-09 21:06:26,763 |  INFO |              Logging |   54 | Starting job: foreachPartition at XGBoost.scala:524
2019-11-09 21:06:26,765 |  INFO |              Logging |   54 | Got job 2 (foreachPartition at XGBoost.scala:524) with 1 output partitions
2019-11-09 21:06:26,765 |  INFO |              Logging |   54 | Final stage: ResultStage 3 (foreachPartition at XGBoost.scala:524)
2019-11-09 21:06:26,765 |  INFO |              Logging |   54 | Parents of final stage: List()
2019-11-09 21:06:26,768 |  INFO |              Logging |   54 | Missing parents: List()
2019-11-09 21:06:26,769 |  INFO |              Logging |   54 | Submitting ResultStage 3 (MapPartitionsRDD[18] at mapPartitions at XGBoost.scala:409), which has no missing parents
2019-11-09 21:06:26,808 |  INFO |              Logging |   54 | Block broadcast_6 stored as values in memory (estimated size 40.3 KB, free 4.1 GB)
2019-11-09 21:06:26,811 |  INFO |              Logging |   54 | Block broadcast_6_piece0 stored as bytes in memory (estimated size 18.9 KB, free 4.1 GB)
2019-11-09 21:06:26,812 |  INFO |              Logging |   54 | Added broadcast_6_piece0 in memory on DESKTOP-4869294:60665 (size: 18.9 KB, free: 4.1 GB)
2019-11-09 21:06:26,813 |  INFO |              Logging |   54 | Created broadcast 6 from broadcast at DAGScheduler.scala:1161
2019-11-09 21:06:26,814 |  INFO |              Logging |   54 | Submitting 1 missing tasks from ResultStage 3 (MapPartitionsRDD[18] at mapPartitions at XGBoost.scala:409) (first 15 tasks are for partitions Vector(0))
2019-11-09 21:06:26,814 |  INFO |              Logging |   54 | Adding task set 3.0 with 1 tasks
2019-11-09 21:06:26,816 |  INFO |              Logging |   54 | Starting task 0.0 in stage 3.0 (TID 3, localhost, executor driver, partition 0, PROCESS_LOCAL, 7786 bytes)
2019-11-09 21:06:26,816 |  INFO |              Logging |   54 | Running task 0.0 in stage 3.0 (TID 3)
2019-11-09 21:06:26,905 |  INFO |              Logging |   54 | Code generated in 12.1707 ms
2019-11-09 21:06:27,118 |  INFO |              Logging |   54 | Reading File path: file:///C:/Data/iris.data.csv, range: 0-4551, partition values: [empty row]
[21:06:27] DEBUG: C:\GIT\xgboost\src\gbm\gbtree.cc:82: Using updaters: grow_colmaker,prune
[21:06:27] DEBUG: C:\GIT\xgboost\src\gbm\gbtree.cc:138: Using tree method: 2
[0]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 4 extra nodes, 0 pruned nodes, max_depth=2
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 10 extra nodes, 0 pruned nodes, max_depth=3
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[1]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[2]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[3]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[4]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[5]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=5
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[6]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[7]	train-merror:0.020000
[8]	train-merror:0.020000
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=5
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 10 extra nodes, 0 pruned nodes, max_depth=3
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 10 extra nodes, 0 pruned nodes, max_depth=3
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 2 extra nodes, 0 pruned nodes, max_depth=1
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 12 extra nodes, 0 pruned nodes, max_depth=4
[21:06:27] INFO: C:\GIT\xgboost\src\tree\updater_prune.cc:78: tree pruning end, 1 roots, 10 extra nodes, 0 pruned nodes, max_depth=3
2019-11-09 21:06:27,204 |  INFO |              Logging |   54 | Block rdd_18_0 stored as values in memory (estimated size 224.0 B, free 4.1 GB)
2019-11-09 21:06:27,205 |  INFO |              Logging |   54 | Added rdd_18_0 in memory on DESKTOP-4869294:60665 (size: 224.0 B, free: 4.1 GB)
2019-11-09 21:06:27,220 |  INFO |              Logging |   54 | 1 block locks were not released by TID = 3:
[rdd_18_0]
2019-11-09 21:06:27,222 |  INFO |              Logging |   54 | Finished task 0.0 in stage 3.0 (TID 3). 1361 bytes result sent to driver
2019-11-09 21:06:27,223 |  INFO |              Logging |   54 | Finished task 0.0 in stage 3.0 (TID 3) in 407 ms on localhost (executor driver) (1/1)
2019-11-09 21:06:27,223 |  INFO |              Logging |   54 | Removed TaskSet 3.0, whose tasks have all completed, from pool
2019-11-09 21:06:27,224 |  INFO |              Logging |   54 | ResultStage 3 (foreachPartition at XGBoost.scala:524) finished in 0.453 s
2019-11-09 21:06:27,224 |  INFO |              Logging |   54 | Job 2 finished: foreachPartition at XGBoost.scala:524, took 0.461351 s
2019-11-09 21:06:46,794 |  INFO |             XGBoost$ |  530 | Rabit returns with exit code 3
2019-11-09 21:06:46,795 | ERROR |             XGBoost$ |  550 | the job was aborted due to
ml.dmlc.xgboost4j.java.XGBoostError: XGBoostModel training failed
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.postTrackerReturnProcessing(XGBoost.scala:655)
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.$anonfun$trainDistributed$1(XGBoost.scala:532)
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.$anonfun$trainDistributed$1$adapted(XGBoost.scala:507)
	at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:234)
	at scala.collection.immutable.List.foreach(List.scala:389)
	at scala.collection.TraversableLike.map(TraversableLike.scala:234)
	at scala.collection.TraversableLike.map$(TraversableLike.scala:227)
	at scala.collection.immutable.List.map(List.scala:295)
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.trainDistributed(XGBoost.scala:506)
	at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:191)
	at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:40)
	at org.apache.spark.ml.Predictor.fit(Predictor.scala:118)
	at SimpleXGBoost$.delayedEndpoint$SimpleXGBoost$1(SimpleXGBoost.scala:49)
	at SimpleXGBoost$delayedInit$body.apply(SimpleXGBoost.scala:6)
	at scala.Function0.apply$mcV$sp(Function0.scala:34)
	at scala.Function0.apply$mcV$sp$(Function0.scala:34)
	at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
	at scala.App.$anonfun$main$1$adapted(App.scala:76)
	at scala.collection.immutable.List.foreach(List.scala:389)
	at scala.App.main(App.scala:76)
	at scala.App.main$(App.scala:74)
	at SimpleXGBoost$.main(SimpleXGBoost.scala:6)
	at SimpleXGBoost.main(SimpleXGBoost.scala)
2019-11-09 21:06:46,807 |  INFO |    AbstractConnector |  318 | Stopped Spark@6d0b5baf{HTTP/1.1,[http/1.1]}{<IP_ADDRESS>:4040}
2019-11-09 21:06:46,809 |  INFO |              Logging |   54 | Stopped Spark web UI at http://DESKTOP-4869294:4040
2019-11-09 21:06:46,828 |  INFO |              Logging |   54 | MapOutputTrackerMasterEndpoint stopped!
2019-11-09 21:06:46,860 |  INFO |              Logging |   54 | MemoryStore cleared
2019-11-09 21:06:46,861 |  INFO |              Logging |   54 | BlockManager stopped
2019-11-09 21:06:46,862 |  INFO |              Logging |   54 | BlockManagerMaster stopped
2019-11-09 21:06:46,865 |  INFO |              Logging |   54 | OutputCommitCoordinator stopped!
2019-11-09 21:06:46,868 |  INFO |              Logging |   54 | Successfully stopped SparkContext
Exception in thread "main" ml.dmlc.xgboost4j.java.XGBoostError: XGBoostModel training failed
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.postTrackerReturnProcessing(XGBoost.scala:655)
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.$anonfun$trainDistributed$1(XGBoost.scala:532)
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.$anonfun$trainDistributed$1$adapted(XGBoost.scala:507)
	at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:234)
	at scala.collection.immutable.List.foreach(List.scala:389)
	at scala.collection.TraversableLike.map(TraversableLike.scala:234)
	at scala.collection.TraversableLike.map$(TraversableLike.scala:227)
	at scala.collection.immutable.List.map(List.scala:295)
	at ml.dmlc.xgboost4j.scala.spark.XGBoost$.trainDistributed(XGBoost.scala:506)
	at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:191)
	at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:40)
	at org.apache.spark.ml.Predictor.fit(Predictor.scala:118)
	at SimpleXGBoost$.delayedEndpoint$SimpleXGBoost$1(SimpleXGBoost.scala:49)
	at SimpleXGBoost$delayedInit$body.apply(SimpleXGBoost.scala:6)
	at scala.Function0.apply$mcV$sp(Function0.scala:34)
	at scala.Function0.apply$mcV$sp$(Function0.scala:34)
	at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
	at scala.App.$anonfun$main$1$adapted(App.scala:76)
	at scala.collection.immutable.List.foreach(List.scala:389)
	at scala.App.main(App.scala:76)
	at scala.App.main$(App.scala:74)
	at SimpleXGBoost$.main(SimpleXGBoost.scala:6)
	at SimpleXGBoost.main(SimpleXGBoost.scala)
2019-11-09 21:06:46,871 |  INFO |              Logging |   54 | Shutdown hook called
2019-11-09 21:06:46,872 |  INFO |              Logging |   54 | Deleting directory C:\Users\simon\AppData\Local\Temp\spark-3c885b32-7eac-4905-8ba5-ef9777f61e23
[9]	train-merror:0.020000

Process finished with exit code 1

It all begins to hang, specifically after the lines:
2019-11-09 21:06:27,224 |  INFO |              Logging |   54 | ResultStage 3 (foreachPartition at XGBoost.scala:524) finished in 0.453 s
2019-11-09 21:06:27,224 |  INFO |              Logging |   54 | Job 2 finished: foreachPartition at XGBoost.scala:524, took 0.461351 s

Then once the tracker times out, it logs the rest of what you can see in the stack trace.
What have you tried?
I looked around a number of issues, specifically these two which seem the closest to my problem:

https://github.com/dmlc/xgboost/issues/2780
https://github.com/dmlc/xgboost/issues/2352

From these issues I have tried a number of suggestions:

Using both the python and scala trackers.
Both publishing jars to local maven repository and adding as unmanaged jars.
Tried training on the suggested Iris data set, as well as my own data sets.
Adding an xgboost-tracker.properties file under resources, with the line specifying host-ip as localhost, 127.0.01, my computer name, computer ip, etc
Switching off Anti-virus/Firewalls
Mix and matching different Scala 2.12.[4, 8] and Spark  2.4.[0-4] versions in build.sbt
Tinkering around with Spark and XGBoost parameters, namely:
a) Spark setting local[s] and XGBoost setting num_workers=w ensuring that s >= w) and
b) Setting XGBoost settings num_early_stopping_rounds=5, disable_default_eval_metric=1, and maximize_evaluation_metrics=true to force an early end to the rounds

None of the above worked, however if I build the jars in Linux against Scala 2.12.4, and run the exact same code, everything works fine - so this issue seems to be Windows specific, in regards to communication with Spark running locally.
Is there something else I could try or something I have overlooked to get around this issue? Also are there any plans to build XGBoost4j(-spark) against Scala 2.12 at https://github.com/criteo-forks/xgboost-jars/releases in the near future?
Many thanks in advance, please let me know if I can provide more info/context.

Thanks for the detailed report.  For running on Windows with distributed training please try latest master branch.  But in general most of the tests are done on Linux.


Vision 4in1 Multisensor issues

I have a Vision 4in1 Multisensor that worked fine in the old Zwave integration in Home assistant, but is not fully identified in Zwave JS. Wondering if it needs to be added to the database? I've attached the manual. Anyone else having issues?
vision_4in1_door_window_sensor.pdf

Hi @larrygoodstuff,
We somewhat need more information to be able to help.
Please could you follow the issue template here.


NetworkIdentity & NetworkVisibility Should Not Be Toggling Renderers

Describe the bug
The NetworkIdentity component has code to turn off renderers in OnSetHostVisibility in the most recent Mirror update. This had several breaks in our product and caused 2 weeks of bug finding.  Mirror is a great networking library, but it should not be dealing with culling as that's something the game's LOD engine should be handling. This is scope creep beyond what Mirror's core responsibilities are.

How can we reproduce the issue, step by step:
See above code sample
Expected behavior
No component inside Mirror's networking layers should be enabling or disabling renderers. This is scope creep beyond what Mirror is supposed to do.  Instead, provide components that users can add if they want this to turn the renderers off, but do not have NetworkIdentity do this.
Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):
All Platforms
All Targets
All Unity Versions
Most recent Unity (about 3-4 weeks ago)

previously this was in NetworkProximityChecker.
for the new global interest management, we temporarily had to move it into NetworkIdentity.
a couple days ago it was already moved into InterestManagement.cs as virtual function:

In other words, if you use global interest management with one component on Networkmanager, then simply overwrite that function :)

Great, so it’s fixed in a newer version?
Gabe

On Jul 23, 2021, at 8:13 PM, vis2k @.***> wrote:

previously this was in NetworkProximityChecker.
for the new global interest management, we temporarily had to move it into NetworkIdentity.
a couple days ago it was already moved into InterestManagement.cs as virtual function:
In other words, if you use global interest management with one component on Networkmanager, then simply overwrite that function :)
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Can i still contribute?

Hello,
I hope you're doing well. I have a question about contributing to this repository. Can I still contribute?
Thank you.

Yes. I realized this project got some traction lately and I will also work on removing the javascript references (since it was initially copied from JS) and adding more java examples. You're welcome to help


framework doesn't run properly in browser

Sir, could you please resolve this issue? I have installed this framework in Clein Kali Linux (2023.3), but I cannot get it to run in the browser, and I cannot add domains to the framework. The framework was suddenly stuck, and I cannot operate. If you have solved this issue, I would like to thank you. This framework helps me a lot, and I need it a lot.

Okay, first, you need to stop spamming this Framework with Issues and comments on other issues.  You are making it incredibly difficult for me to keep track of individual issues.  Other people may have issues that appear to be the same of yours, but they are not.  You are causing confusion within our community.
I will repeat my response to one of your many other comments on other issues:
Please provide me with as much information as possible about how your use-case may be unique from other members of the community.  Your PC, virtualization software, processor architecture, anything at all that could help me identify why the framework is not working for you specifically.
I also strongly recommend you review GitHub's Community Guidelines around submitting Issues for open-source projects.  The way you have chosen to conduct yourself here has made it very difficult for me to want to invest my free time helping you succeed.

@0xmkr24 That question has been answered many times and does not pertain to the original issue.


(Suggestion) Add a config option to disable giving read me at start

Or is there an already existing option?

Why do you need that?

I want a cleaner starting inventory. For a map.

I have to agree with JAWSAWN, I prefer to be able to start without forced mod items in my inventory when building a pack.  Please make it an option to disable the read me at start.

Implemented next release (new 'spawnNote' config option)