] 35777477K->6247187K(105758720K), 0.0929561 secs] [Times: user=1.27 sys=0.00, real=0.09 secs]
ects are masked from ‘package:dplyr’:
between, first, last
The following object is masked from ‘package:purrr’:
transpose
Attaching package: ‘lubridate’
The following objects are masked from ‘package:data.table’:
hour, isoweek, mday, minute, month, quarter, second, wday, week,
yday, year
The following objects are masked from ‘package:base’:
date, intersect, setdiff, union
Attaching package: ‘sparklyr’
The following object is masked from ‘package:purrr’:
invoke
----------------------------------------------------------------------
Your next step is to start H2O:
> h2o.init()
For H2O package documentation, ask for help:
> ??h2o
After starting H2O, you can use the Web UI at http://localhost:54321
For more information visit https://docs.h2o.ai
----------------------------------------------------------------------
Attaching package: ‘h2o’
The following objects are masked from ‘package:lubridate’:
day, hour, month, week, year
The following objects are masked from ‘package:data.table’:
hour, month, week, year
The following objects are masked from ‘package:stats’:
cor, sd, var
The following objects are masked from ‘package:base’:
&&, %*%, %in%, ||, apply, as.factor, as.numeric, colnames,
colnames<-, ifelse, is.character, is.factor, is.numeric, log,
log10, log1p, log2, round, signif, trunc
Attaching package: ‘SparkR’
The following object is masked _by_ ‘.GlobalEnv’:
setLocalProperty
The following objects are masked from ‘package:h2o’:
colnames, colnames<-, hour, month, sd, summary, var, year
The following object is masked from ‘package:sparklyr’:
collect
The following objects are masked from ‘package:lubridate’:
hour, intersect, minute, month, quarter, second, union, year
The following objects are masked from ‘package:data.table’:
between, cube, first, hour, last, like, minute, month, quarter,
rollup, second, tables, year
The following objects are masked from ‘package:dplyr’:
arrange, between, coalesce, collect, contains, count, cume_dist,
dense_rank, desc, distinct, explain, expr, filter, first, group_by,
intersect, lag, last, lead, mutate, n, n_distinct, ntile,
percent_rank, rename, row_number, sample_frac, select, slice, sql,
summarize, union
The following objects are masked from ‘package:purrr’:
flatten, negate, when
The following object is masked from ‘package:tidyr’:
contains
The following object is masked from ‘package:ggplot2’:
expr
The following objects are masked from ‘package:stats’:
cov, filter, lag, na.omit, predict, sd, var, window
The following objects are masked from ‘package:base’:
as.data.frame, colnames, colnames<-, drop, endsWith, intersect,
rank, rbind, sample, startsWith, subset, summary, transform, union
DATABRICKS_STDOUT_END-be6161dd-abeb-4e4d-a371-d5e896416ca5-1656886899078
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) accepted connection
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) is waiting for sparklyr client to connect to port 65529
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) received command 0
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) found requested session matches current session
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) is creating backend and allocating system resources
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) is using port 65530 for backend channel
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) created the backend
22/07/03 22:21:39 INFO sparklyr: Gateway (65529) is waiting for r process to end
DATABRICKS_STDOUT_END-be6161dd-abeb-4e4d-a371-d5e896416ca5-1656886899718
Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 39 minutes 54 seconds
H2O cluster timezone: Etc/UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.32.0.4
H2O cluster version age: 1 year, 5 months and 2 days !!!
H2O cluster name: sparkling-water-root_app-20220703213409-0000
H2O cluster total nodes: 4
H2O cluster total memory: 149.14 GB
H2O cluster total cores: 64
H2O cluster allowed cores: 64
H2O cluster healthy: TRUE
H2O Connection ip:
H2O Connection port: 9009
H2O Connection proxy: NA
H2O Internal Security: FALSE
H2O API Extensions: XGBoost, Algos, Amazon S3, Sparkling Water REST API Extensions, AutoML, Core V3, TargetEncoder, Core V4
R Version: R version 3.6.3 (2020-02-29)
Reference class object of class "H2OContext"
Field "jhc":
<jobj[14]>
ai.h2o.sparkling.H2OContext
Sparkling Water Context:
* Sparkling Water Version: 3.32.0.4-1-3.0
* H2O name: root
* cluster size: 4
* list of used nodes:
(executorId, host, port)
------------------------
------------------------
ERROR: Unexpected HTTP Status code: 500 Server Error (url = http://localhost:54321/99/Rapids)
java.lang.IllegalStateException
[1] "java.lang.IllegalStateException: Ref-count mismatch for vec $04ff96000000ffffffff$_b0e37dde53876a52241ef12bcbad4ded: REFCNT = 9, should be 8"
[2] " water.rapids.Session.sanity_check_refs(Session.java:338)"
[3] " water.rapids.Session.exec(Session.java:87)"
[4] " water.rapids.Rapids.exec(Rapids.java:94)"
[5] " water.api.RapidsHandler.exec(RapidsHandler.java:38)"
[6] " sun.reflect.GeneratedMethodAccessor422.invoke(Unknown Source)"
[7] " sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)"
[8] " java.lang.reflect.Method.invoke(Method.java:498)"
[9] " water.api.Handler.handle(Handler.java:60)"
[10] " water.api.RequestServer.serve(RequestServer.java:470)"
[11] " water.api.RequestServer.doGeneric(RequestServer.java:301)"
[12] " water.api.RequestServer.doPost(RequestServer.java:227)"
[13] " javax.servlet.http.HttpServlet.service(HttpServlet.java:707)"
[14] " javax.servlet.http.HttpServlet.service(HttpServlet.java:790)"
[15] " ai.h2o.org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:865)"
[16] " ai.h2o.org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:535)"
[17] " ai.h2o.org.eclipse.jetty.server.handler.ScopedHandler.nextHandle(ScopedHandler.java:255)"
[18] " ai.h2o.org.eclipse.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1317)"
[19] " ai.h2o.org.eclipse.jetty.server.handler.ScopedHandler.nextScope(ScopedHandler.java:203)"
[20] " ai.h2o.org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:473)"
[21] " ai.h2o.org.eclipse.jetty.server.handler.ScopedHandler.nextScope(ScopedHandler.java:201)"
[22] " ai.h2o.org.eclipse.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1219)"
[23] " ai.h2o.org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:144)"
[24] " ai.h2o.org.eclipse.jetty.server.handler.HandlerCollection.handle(HandlerCollection.java:126)"
[25] " ai.h2o.org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:132)"
[26] " water.webserver.jetty9.Jetty9ServerAdapter$LoginHandler.handle(Jetty9ServerAdapter.java:130)"
[27] " ai.h2o.org.eclipse.jetty.server.handler.HandlerCollection.handle(HandlerCollection.java:126)"
[28] " ai.h2o.org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:132)"
[29] " ai.h2o.org.eclipse.jetty.server.Server.handle(Server.java:531)"
[30] " ai.h2o.org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:352)"
[31] " ai.h2o.org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:260)"
[32] " ai.h2o.org.eclipse.jetty.io.AbstractConnection$ReadCallback.succeeded(AbstractConnection.java:281)"
[33] " ai.h2o.org.eclipse.jetty.io.FillInterest.fillable(FillInterest.java:102)"
[34] " ai.h2o.org.eclipse.jetty.io.ChannelEndPoint$2.run(ChannelEndPoint.java:118)"
[35] " ai.h2o.org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.runTask(EatWhatYouKill.java:333)"
[36] " ai.h2o.org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.doProduce(EatWhatYo
In addition: There were 50 or more warnings (use warnings() to see the first 50)
DATABRICKS_STDOUT_END-be6161dd-abeb-4e4d-a371-d5e896416ca5-1656894022704