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- About Jan-Tschada
%20Office%20skaliert.png "Jan-Tschada"){kind=avatar}
Jan-Tschada
Esri Contributor
since
07-04-2014
3 weeks ago
130
Posts created
31
Kudos given
7
Solutions
94
Kudos received
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My Ideas
(2 Idea Submissions)Latest Contributions by Jan-Tschada
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POST
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Are there any best practices how to implement NTLM authentication with a GP Service so that, the valid user token using Single Sign On (SSO) with ArcGIS Enterprise is used for requesting another web service consumed by the Python tool being published as GP Service. Use Case: We are querying a custom graph database using NTLM authentication with Python (request-ntlm module) and transforming the entities and relations to features having relationships into a geodatabase on the fly. SSO works like a charm with ArcGIS Pro. But, when we publish the GP Tool as a GP Service, the service runs using the service account of the federated ArcGIS Server. The service needs to use the SSO token of the user which requested the GP Service call e.g. from any ArcGIS client. Is there any workflow how to reuse the SSO token using Python or at least to get the user info which requested the GP Service call? Any help would be fine.
... View more
08-20-2021
02:46 AM
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0
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0
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1493
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POST
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Very nice. We usually just upgrade existing projects and were not aware of this great enhancement. I just started to get my hands dirty and saw some linker warnings regarding the EsriRuntimeQtd.pdb not being linked with EsriRuntimeQtd.lib(LicenseResult.obj) and the other related *.obj's on Windows. But anyway, this CMake support helps us a lot and should make it to the official website. Otherwise we would not be able to deliver our DevOps release pipeline by integrating our CMake based vcpkg packages.
... View more
08-11-2021
05:49 AM
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0
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0
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2812
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POST
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We are integrating a bunch of C++ utility libraries into our ArcGIS Runtime for Qt Quick based sample viewer. Usually these C++ utility libraries are compiled using CMake. The Qt company offers some samples using Qt Quick with CMake. cmake_minimum_required(VERSION 3.14)
project(QPyApp LANGUAGES CXX)
set(CMAKE_INCLUDE_CURRENT_DIR ON)
set(CMAKE_AUTOUIC ON)
set(CMAKE_AUTOMOC ON)
set(CMAKE_AUTORCC ON)
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
# QtCreator supports the following variables for Android, which are identical to qmake Android variables.
# Check https://doc.qt.io/qt/deployment-android.html for more information.
# They need to be set before the find_package(...) calls below.
#if(ANDROID)
# set(ANDROID_PACKAGE_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}/android")
# if (ANDROID_ABI STREQUAL "armeabi-v7a")
# set(ANDROID_EXTRA_LIBS
# ${CMAKE_CURRENT_SOURCE_DIR}/path/to/libcrypto.so
# ${CMAKE_CURRENT_SOURCE_DIR}/path/to/libssl.so)
# endif()
#endif()
find_package(QT NAMES Qt6 Qt5 COMPONENTS Core Quick REQUIRED)
find_package(Qt${QT_VERSION_MAJOR} COMPONENTS Core Quick REQUIRED)
set(PROJECT_SOURCES
main.cpp
qml.qrc
)
if(${QT_VERSION_MAJOR} GREATER_EQUAL 6)
qt_add_executable(QPyApp
${PROJECT_SOURCES}
)
else()
if(ANDROID)
add_library(QPyApp SHARED
${PROJECT_SOURCES}
)
else()
add_executable(QPyApp
${PROJECT_SOURCES}
)
endif()
endif()
target_compile_definitions(QPyApp
PRIVATE $<$<OR:$<CONFIG:Debug>,$<CONFIG:RelWithDebInfo>>:QT_QML_DEBUG>)
target_link_libraries(QPyApp
PRIVATE Qt${QT_VERSION_MAJOR}::Core Qt${QT_VERSION_MAJOR}::Quick) Would you be so kind and provide a sample using CMake and share it using arcgis-runtime-samples-qt
... View more
08-10-2021
08:13 AM
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0
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2
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2851
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POST
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We finally figured it out, also we have to use singleLayerSelectedCondition instead of singleFeatureLayerSelectedCondition for enabling it. <conditions>
<insertCondition id="esri_mapping_single_layer_selected">
<and>
<state id="esri_mapping_singleLayerSelectedCondition"/>
</and>
</insertCondition>
<insertCondition id="esri_mapping_single_standalonetable_selected">
<and>
<state id="esri_mapping_singleStandaloneTableSelectedCondition"/>
</and>
</insertCondition>
</conditions>
<updateModule refID="esri_mapping">
<menus>
<updateMenu refID="esri_mapping_layerContextMenu">
<insertButton refID="SDA_Pro_Module_Create_Sda_From_FeatureTable_Button" separator="false" placeWith="esri_editing_table_openTablePaneButton" insert="after" />
</updateMenu>
<updateMenu refID="esri_mapping_unregisteredLayerContextMenu">
<insertButton refID="SDA_Pro_Module_Create_Sda_From_FeatureTable_Button" separator="false" placeWith="esri_editing_table_openTablePaneButton" insert="after" />
</updateMenu>
<updateMenu refID="esri_mapping_standaloneTableContextMenu">
<insertButton refID="SDA_Pro_Module_Create_Sda_From_StandaloneTable_Button" separator="false" placeWith="esri_editing_table_openStandaloneTablePaneButton" insert="after" />
</updateMenu>
<updateMenu refID="esri_mapping_unregisteredStandaloneTableContextMenu">
<insertButton refID="SDA_Pro_Module_Create_Sda_From_StandaloneTable_Button" separator="false" placeWith="esri_editing_table_openStandaloneTablePaneButton" insert="after" />
</updateMenu>
</menus>
</updateModule> Using unregistered context menu did the trick. See Solved: Buttons built by ArcGIS Pro SDK cannot be added to... - Esri Community
... View more
07-08-2021
04:26 AM
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1
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0
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2084
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POST
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We need to add a custom button to the context menu for feature layers. In the past we used esri_mapping_layerContextMenu and esri_mapping_standaloneTableContextMenu. We define the state as insert conditions for layers and standalone tables by using: <state id="esri_mapping_singleLayerSelectedCondition"/> <state id="esri_mapping_singleFeatureLayerSelectedCondition"/> <state id="esri_mapping_singleStandaloneTableSelectedCondition"/> With ArcGIS Pro 2.7 and 2.8 esri_mapping_layerContextMenu seems not to work for any shapefile related layers, any help would be appropriated.
... View more
07-08-2021
03:52 AM
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0
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1
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2115
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POST
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We would love to see in-memory layer with property label graph support, not only m:n relationship classes and this in-memory representation should be using SPARQL for connecting various graph datasources. Unluckily, as a distributor I cannot create ArcGIS Ideas.
... View more
05-18-2021
05:24 AM
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0
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0
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2813
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POST
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We are trying to reconstruct tracks using AIS data and our GeoAnalytics Server fail with some "Request Entity Too Large" during mapping the partitions. As far as we can judge it, sparks wants to write into the BDFS being based on Elasticsearch. Maybe we need to define some spark configuration to adjust the size of the data being written? {"messageCode":"BD_101029","message":"193/372 distributed tasks completed.","params":{"completedTasks":"193","totalTasks":"372"}}
[ERROR|09:01:47] Stage 'runJob at EsSpark.scala:108' failed in GeoAnalytics job (attempt=0): Job aborted due to stage failure: Task 9 in stage 1.0 failed 4 times, most recent failure: Lost task 9.3 in stage 1.0 (TID 207, ##.##.##.###:####, executor 1): org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:]
at org.elasticsearch.hadoop.rest.RestClient.checkResponse(RestClient.java:477)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:434)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:428)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:408)
at org.elasticsearch.hadoop.rest.RestClient.bulk(RestClient.java:226)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.tryFlush(BulkProcessor.java:215)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.flush(BulkProcessor.java:518)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.add(BulkProcessor.java:132)
at org.elasticsearch.hadoop.rest.RestRepository.doWriteToIndex(RestRepository.java:192)
at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:172)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:77)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1$adapted(EsSpark.scala:108)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:.
{"messageCode":"BD_101030","message":"Failed to execute ReconstructTracks. Please contact your administrator with job ID 'jedad0ac11f654d64bc31ecc732c295be'.","params":{"toolName":"ReconstructTracks","jobID":"jedad0ac11f654d64bc31ecc732c295be"}}
[ERROR|09:01:47] Job 'jedad0ac11f654d64bc31ecc732c295be' for tool 'ReconstructTracks' failed: Job aborted due to stage failure: Task 9 in stage 1.0 failed 4 times, most recent failure: Lost task 9.3 in stage 1.0 (TID 207, ##.##.##.###, executor 1): org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:]
at org.elasticsearch.hadoop.rest.RestClient.checkResponse(RestClient.java:477)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:434)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:428)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:408)
at org.elasticsearch.hadoop.rest.RestClient.bulk(RestClient.java:226)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.tryFlush(BulkProcessor.java:215)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.flush(BulkProcessor.java:518)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.add(BulkProcessor.java:132)
at org.elasticsearch.hadoop.rest.RestRepository.doWriteToIndex(RestRepository.java:192)
at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:172)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:77)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1$adapted(EsSpark.scala:108)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:. [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:].
[DEBUG|09:01:47] Job 'jedad0ac11f654d64bc31ecc732c295be' for tool 'ReconstructTracks' failed: Job aborted due to stage failure: Task 9 in stage 1.0 failed 4 times, most recent failure: Lost task 9.3 in stage 1.0 (TID 207, ##.##.##.###, executor 1): org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:]
at org.elasticsearch.hadoop.rest.RestClient.checkResponse(RestClient.java:477)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:434)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:428)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:408)
at org.elasticsearch.hadoop.rest.RestClient.bulk(RestClient.java:226)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.tryFlush(BulkProcessor.java:215)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.flush(BulkProcessor.java:518)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.add(BulkProcessor.java:132)
at org.elasticsearch.hadoop.rest.RestRepository.doWriteToIndex(RestRepository.java:192)
at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:172)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:77)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1$adapted(EsSpark.scala:108)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:. [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:].
Job aborted due to stage failure: Task 9 in stage 1.0 failed 4 times, most recent failure: Lost task 9.3 in stage 1.0 (TID 207, 10.23.35.141, executor 1): org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:]
at org.elasticsearch.hadoop.rest.RestClient.checkResponse(RestClient.java:477)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:434)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:428)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:408)
at org.elasticsearch.hadoop.rest.RestClient.bulk(RestClient.java:226)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.tryFlush(BulkProcessor.java:215)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.flush(BulkProcessor.java:518)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.add(BulkProcessor.java:132)
at org.elasticsearch.hadoop.rest.RestRepository.doWriteToIndex(RestRepository.java:192)
at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:172)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:77)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1$adapted(EsSpark.scala:108)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
[DEBUG]org.apache.spark.SparkException: Job aborted due to stage failure: Task 9 in stage 1.0 failed 4 times, most recent failure: Lost task 9.3 in stage 1.0 (TID 207, ##.##.##.###, executor 1): org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:]
at org.elasticsearch.hadoop.rest.RestClient.checkResponse(RestClient.java:477)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:434)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:428)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:408)
at org.elasticsearch.hadoop.rest.RestClient.bulk(RestClient.java:226)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.tryFlush(BulkProcessor.java:215)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.flush(BulkProcessor.java:518)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.add(BulkProcessor.java:132)
at org.elasticsearch.hadoop.rest.RestRepository.doWriteToIndex(RestRepository.java:192)
at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:172)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:77)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1$adapted(EsSpark.scala:108)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2152)
at org.elasticsearch.spark.rdd.EsSpark$.doSaveToEs(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.saveToEs(EsSpark.scala:79)
at org.elasticsearch.spark.rdd.EsSpark$.saveToEs(EsSpark.scala:76)
at org.elasticsearch.spark.package$SparkRDDFunctions.saveToEs(package.scala:56)
at com.esri.arcgis.bds.spark.BDSSpark$.saveFeaturesToBDS(BDSSpark.scala:390)
at com.esri.arcgis.bds.spark.BDSSpark$.saveFeaturesToBDS(BDSSpark.scala:238)
at com.esri.arcgis.gae.gp.ags.SpatiotemporalDataStoreWriter.$anonfun$writeOnce$1(SpatiotemporalDataStoreWriter.scala:342)
at scala.util.Try$.apply(Try.scala:213)
at com.esri.arcgis.gae.gp.ags.SpatiotemporalDataStoreWriter.writeOnce(SpatiotemporalDataStoreWriter.scala:300)
at com.esri.arcgis.gae.ags.datastore.managed.ManagedDataStoreWriter.writeAll(ManagedDataStoreWriter.scala:13)
at com.esri.arcgis.gae.ags.datastore.managed.ManagedDataStoreWriter.writeAll$(ManagedDataStoreWriter.scala:8)
at com.esri.arcgis.gae.gp.ags.SpatiotemporalDataStoreWriter.writeAll(SpatiotemporalDataStoreWriter.scala:29)
at com.esri.arcgis.gae.ags.layer.output.ManagedLayerResultManager.addResultLayer(ManagedLayerResultManager.scala:214)
at com.esri.arcgis.gae.gp.adapt.param.LayerOutputConverter.writeToManagedDataStore(LayerOutputConverter.scala:85)
at com.esri.arcgis.gae.gp.adapt.param.LayerOutputConverter.write(LayerOutputConverter.scala:31)
at com.esri.arcgis.gae.gp.adapt.param.FeatureRDDOutputConverter.write(FeatureRDDOutputConverter.scala:17)
at com.esri.arcgis.gae.gp.adapt.param.FeatureRDDOutputConverter.write(FeatureRDDOutputConverter.scala:9)
at com.esri.arcgis.gae.gp.adapt.param.GPParameterAdapter$$anon$2.writeParam(GPParameterAdapter.scala:77)
at com.esri.arcgis.gae.fn.api.v1.GAFunctionArgs.update(GAFunctionArgs.scala:53)
at com.esri.arcgis.gae.fn.FnReconstructTracks$.execute(FnReconstructTracks.scala:165)
at com.esri.arcgis.gae.fn.api.v1.GAFunction.executeFunction(GAFunction.scala:25)
at com.esri.arcgis.gae.fn.api.v1.GAFunction.executeFunction$(GAFunction.scala:15)
at com.esri.arcgis.gae.fn.FnReconstructTracks$.executeFunction(FnReconstructTracks.scala:25)
at com.esri.arcgis.gae.gp.GPToGAFunctionAdapter.$anonfun$execute$4(GPToGAFunctionAdapter.scala:157)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.esri.arcgis.st.util.ScopeManager.withScope(ScopeManager.scala:20)
at com.esri.arcgis.st.spark.ExecutionContext.withScope(ExecutionContext.scala:23)
at com.esri.arcgis.st.spark.ExecutionContext.withScope$(ExecutionContext.scala:23)
at com.esri.arcgis.st.spark.GenericExecutionContext.withScope(ExecutionContext.scala:52)
at com.esri.arcgis.gae.gp.GPToGAFunctionAdapter.execute(GPToGAFunctionAdapter.scala:155)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at com.esri.arcgis.interop.NativeObjRef.nativeVtblInvokeNative(Native Method)
at com.esri.arcgis.interop.NativeObjRef.nativeVtblInvoke(Unknown Source)
at com.esri.arcgis.interop.NativeObjRef.invoke(Unknown Source)
at com.esri.arcgis.interop.Dispatch.vtblInvoke(Unknown Source)
at com.esri.arcgis.system.IRequestHandlerProxy.handleStringRequest(Unknown Source)
at com.esri.arcgis.discovery.servicelib.impl.SOThreadBase.handleSoapRequest(SOThreadBase.java:574)
at com.esri.arcgis.discovery.servicelib.impl.DedicatedSOThread.handleRequest(DedicatedSOThread.java:310)
at com.esri.arcgis.discovery.servicelib.impl.SOThreadBase.startRun(SOThreadBase.java:430)
at com.esri.arcgis.discovery.servicelib.impl.DedicatedSOThread.run(DedicatedSOThread.java:166)
Caused by: org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: [PUT] on [/_bulk] failed; server[##.##.##.###:####] returned [413|Request Entity Too Large:]
at org.elasticsearch.hadoop.rest.RestClient.checkResponse(RestClient.java:477)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:434)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:428)
at org.elasticsearch.hadoop.rest.RestClient.execute(RestClient.java:408)
at org.elasticsearch.hadoop.rest.RestClient.bulk(RestClient.java:226)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.tryFlush(BulkProcessor.java:215)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.flush(BulkProcessor.java:518)
at org.elasticsearch.hadoop.rest.bulk.BulkProcessor.add(BulkProcessor.java:132)
at org.elasticsearch.hadoop.rest.RestRepository.doWriteToIndex(RestRepository.java:192)
at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:172)
at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:77)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1(EsSpark.scala:108)
at org.elasticsearch.spark.rdd.EsSpark$.$anonfun$doSaveToEs$1$adapted(EsSpark.scala:108)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
[DEBUG|09:01:47] Running cleanup tasks for conditions (Error,Complete)
[DEBUG|09:01:47] Running cleanup task [? @ DebugUtil.scala:106].
... View more
05-14-2021
02:53 AM
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1
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2410
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We try to write into a registered BDFS named 'BDFS2'. The datastore manager shows the datasetpath as '/bigDataFileShares/BDFS2'. When we try to use it for writing from a custom python script the spark fails with {"messageCode":"BD_101138","message":"[Python] pyspark.sql.utils.IllegalArgumentException: Unsupported output target '/bigDataFileShares/BDFS2'","params":{"text":"pyspark.sql.utils.IllegalArgumentException: Unsupported
output target '/bigDataFileShares/BDFS2'"}} Custom script for writing tracks: def write_tracks(layer_url=None, where=None, output_bdfs=None, output_name=None):
layer_url = user_variables['layer_url']
where = user_variables['where']
output_bdfs = user_variables['output_bdfs']
output_name = user_variables['output_name']
tracks_data = spark.read.format('webgis').option('where', where).load(layer_url)
if None is output_bdfs:
tracks_data.write.format('webgis').save(output_name)
else:
tracks_data.write.format('webgis').option('dataStore', output_bdfs).save(output_name) Do we have to specify a template before writing the filtered dataframe?
... View more
05-11-2021
02:30 AM
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0
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1
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2713
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Currently, we are using the Open Source version of the Qt Framework SDK. The Qt company decided to make the LTS releases only available to commercial licenses. In January the Qt company made the 5.15 LTS readonly for the Open Source version. Any necessary bugfix will only be published into the commercial branch of 5.15 and the latest release e.g. Qt 6.x. Right now, we have to keep up with the "Qt release pace" and always support the latest Qt release when using the Open Source version or risk that serious security issues will not be fixed - which is not a valid option for serious development. The only two options we see so far is to move away from the Open Source version or unluckily pull out the whole Qt technology stack and replace it with some alternatives. I have to discuss that with our sales and business advisors in first place.
... View more
04-09-2021
03:43 AM
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0
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0
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1723
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We would love to deeply integrate knowledge graphs into the ArcGIS Platform. Not only for using knowledge graphs as a kind of custom datastore, much more of gaining spatial insights like graphs showing the spatial relationship e.g. IEDs -> are located near -> main roads -> used by convoi's ... as a kind of intelligence view over all known feature layers.
... View more
04-06-2021
08:06 AM
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0
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2
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3007
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We already got our hands dirty using Qt and .NET Blazor for webassembly development. We saw that the Geometry routines of the new JavaScript API uses webassembly, too. Is there anything planned extending ArcGIS Web App Builders or developing WebApps using webassembly?
... View more
04-06-2021
05:45 AM
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0
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1
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2900
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The Qt guys did a great job getting rid of legacy implementations and uses the native graphics API of each operating system, now. They also made it possible developing Qt Quick Apps without the QML JavaScript runtime. Would you be so kind and tell us when the ArcGIS Runtime for Qt is going to support the new Qt 6 version?
... View more
04-06-2021
05:40 AM
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0
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2
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1817
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Our business partners/system integrators like Atos and SAP would love to see some high performance geospatial engine being implemented in Rust. This geospatial engine should be available on mobile, desktop, server and serverless environments. There is a need for integrating the same geospatial workflows using the same geospatial engine in all environments. Currently the best option so far is GitHub - georust/geo: Geospatial primitives and algorithms for Rust. The geospatial engine should only offer the same methods like the GeometryEngine of ArcGIS Pro and ArcGIS Runtime, but having all the capabilities static linked into one hand-build with pride optimized Rust module.
... View more
04-06-2021
05:34 AM
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0
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1
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3127
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Hi Michael, the "buffer.gpkx" sample is attached to the initial post. We stripped it down to a simple buffer model using features as input and output. We can use all of our GPKX packages in any ArcGIS Pro environment and publish it into any of our ArcGIS Enterprise environments. The input "features" parameter is correctly offered as a "GPFeatureRecordSetLayer". Meanwhile we had to create the following support case Geoprocessing packages created in ArcGIS Pro do not offer Feature Set as input parameter by using ArcGIS Runtime Local Server 100.9 for this blocker.
... View more
01-03-2021
11:17 PM
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0
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2876
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Did anybody used a ArcGIS Pro based Geoprocessing Packages with Features as Input Parameter with the Runtime Local Server 100.9? We are still waiting for any feedback related to this issue... meanwhile the support is trying to find any documentation about "Best Practices for creating Geoprocessing Packages with ArcGIS Pro".
... View more
12-22-2020
06:49 AM
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0
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2927
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My kudoed posts
| Title | Kudos | Posted |
|---|---|---|
| 1 | 04-14-2026 11:54 PM | |
| 1 | 05-22-2025 04:30 AM | |
| 3 | 09-18-2024 11:29 AM | |
| 1 | 07-30-2024 07:55 AM | |
| 1 | 03-13-2024 09:41 AM |
Activity Feed
- Posted ArcGIS is Advancing – Technische Neuerungen für moderne GeoAI Apps on GeoDev Germany Blog. 04-21-2026 05:25 AM
- Got a Kudo for The Power of WebGIS – Neue Funktionen und Demos. 04-15-2026 05:20 AM
- Posted The Power of WebGIS – Neue Funktionen und Demos on GeoDev Germany Blog. 04-14-2026 11:54 PM
- Posted Unser Rückblick auf den Esri European Dev & Tech Summit 2025 on GeoDev Germany Blog. 11-25-2025 01:28 AM
- Got a Kudo for ArcGIS Location Platform leicht gemacht. 05-26-2025 02:53 AM
- Posted ArcGIS Location Platform leicht gemacht on GeoDev Germany Blog. 05-22-2025 04:30 AM
- Posted Rückblick auf den zweiten Tag des Developer & Technology Summit on GeoDev Germany Blog. 03-31-2025 12:59 AM
- Posted Ein Rückblick auf den Developer & Technology Summit: Highlights und Erkenntnisse on GeoDev Germany Blog. 03-31-2025 12:22 AM
- Posted Abkündigung von ArcGIS Maps SDK for Local Server on GeoDev Germany Blog. 03-05-2025 07:50 AM
- Posted Heat Risk Index: Generate Tesselation für unsere räumlichen Analysen on GeoDev Germany Blog. 09-24-2024 01:47 AM
- Tagged Heat Risk Index: Generate Tesselation für unsere räumlichen Analysen on GeoDev Germany Blog. 09-24-2024 01:47 AM
- Tagged Heat Risk Index: Generate Tesselation für unsere räumlichen Analysen on GeoDev Germany Blog. 09-24-2024 01:47 AM
- Posted Heat Risk Index: Initialisieren von ArcGIS mit Python on GeoDev Germany Blog. 09-22-2024 11:00 PM
- Tagged Heat Risk Index: Initialisieren von ArcGIS mit Python on GeoDev Germany Blog. 09-20-2024 08:55 AM
- Tagged Heat Risk Index: Initialisieren von ArcGIS mit Python on GeoDev Germany Blog. 09-20-2024 08:55 AM
- Got a Kudo for Detecting Urban Heat Islands with ArcGIS: A Collaborative Approach. 09-19-2024 07:05 AM
- Got a Kudo for Detecting Urban Heat Islands with ArcGIS: A Collaborative Approach. 09-19-2024 06:17 AM
- Got a Kudo for Detecting Urban Heat Islands with ArcGIS: A Collaborative Approach. 09-19-2024 05:22 AM
- Posted Detecting Urban Heat Islands with ArcGIS: A Collaborative Approach on GeoDev Germany Blog. 09-18-2024 11:29 AM
- Tagged Detecting Urban Heat Islands with ArcGIS: A Collaborative Approach on GeoDev Germany Blog. 09-18-2024 11:29 AM
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