shc | Apache Spark - Apache HBase Connector
kandi X-RAY | shc Summary
kandi X-RAY | shc Summary
The Apache Spark - Apache HBase Connector is a library to support Spark accessing HBase table as external data source or sink. With it, user can operate HBase with Spark-SQL on DataFrame and DataSet level. With the DataFrame and DataSet support, the library leverages all the optimization techniques in catalyst, and achieves data locality, partition pruning, predicate pushdown, Scanning and BulkGet, etc.
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QUESTION
I tried the following agglomerative clustering in the Jupyter notebook.
The shape of my dataset is (406829, 8)
.
I Tried the following code:
...ANSWER
Answered 2021-May-30 at 17:10Memory consumption of AgglomerativeClustering is O(n²), it means it grows exponentially compared to data size. With single
linkage, the computation can be made faster from O(n³) to O(n²) but unfortunately this does not apply to memory [1]. Single clustering also has down sides of "rich get richer" kind of behavior where the clusters tend to have only a few big ones and others near to zero size clusters [2]. So, at least inside scipy or scikit options on fine tuning are not good.
Another option would be have less input data when fitting the model (= making the training). For that you could use for data frame a method (assuming the data
object is a dataframe):
QUESTION
I wrote a shellcode in C that pops a messagebox. I have compiled two variations of it. One says "Hello World!" (shellcodeA) and the other one says "Goodbye World!" (shellcodeB).
...ANSWER
Answered 2021-May-19 at 13:43I don't know where you see the value 0x119, but BYTE bootstrap[12]
is a BYTE
array.
So assigning bootstrap[i++] = sizeof(bootstrap) + shellcodeALength - i - 4;
will store the lowest byte of the expression in bootstrap[i++]
and ignore the rest, hence can never go above 255.
You probably want something like this instead:
QUESTION
I'm trying to execute a Pyspark statement that writes to BigTable within a Python for loop, which leads to the following error (job submitted using Dataproc). Any client not properly closed (as suggested here) and if yes, any way to do so in Pyspark ?
Note that manually re-executing the script each time with a new Dataproc job works fine, so the job itself is correct.
Thanks for your support !
Pyspark script
...ANSWER
Answered 2021-Jan-11 at 20:13If you are not using the latest version, try updating to it. It looks similar to this issue that was fixed recently. I would imagine the error message still showing up, but the job now finishing means that the support team is still working on it and hopefully they will fix it in the next release.
QUESTION
I'm trying to test the Spark-HBase connector in the GCP context and tried to follow [1], which asks to locally package the connector [2] using Maven (I tried Maven 3.6.3) for Spark 2.4, and leads to following issue.
Error "branch-2.4":
[ERROR] Failed to execute goal net.alchim31.maven:scala-maven-plugin:3.2.2:compile (scala-compile-first) on project shc-core: Execution scala-compile-first of goal net.alchim31.maven:scala-maven-plugin:3.2.2:compile failed.: NullPointerException -> [Help 1]
References
[1] https://github.com/GoogleCloudPlatform/cloud-bigtable-examples/tree/master/scala/bigtable-shc
[2] https://github.com/hortonworks-spark/shc/tree/branch-2.4
...ANSWER
Answered 2020-Dec-27 at 13:58As suggested in the comments (thanks @Ismail !), using Java 8 works to build the connector:
sdk use java 8.0.275-zulu
mvn clean package -DskipTests
One can then import the jar in Dependencies.scala
of the GCP template as follows.
QUESTION
I'm trying to run the Dataproc Bigtable Spark-HBase Connector Example, and get following error when submitting the job.
Any idea ?
Thanks for your support
Command
(base) gcloud dataproc jobs submit spark --cluster $SPARK_CLUSTER --class com.example.bigtable.spark.shc.BigtableSource --jars target/scala-2.11/cloud-bigtable-dataproc-spark-shc-assembly-0.1.jar --region us-east1 -- $BIGTABLE_TABLE
Error
Job [d3b9107ae5e2462fa71689cb0f5909bd] submitted. Waiting for job output... 20/12/27 12:50:10 INFO org.spark_project.jetty.util.log: Logging initialized @2475ms 20/12/27 12:50:10 INFO org.spark_project.jetty.server.Server: jetty-9.3.z-SNAPSHOT, build timestamp: unknown, git hash: unknown 20/12/27 12:50:10 INFO org.spark_project.jetty.server.Server: Started @2576ms 20/12/27 12:50:10 INFO org.spark_project.jetty.server.AbstractConnector: Started ServerConnector@3e6cb045{HTTP/1.1,[http/1.1]}{0.0.0.0:4040} 20/12/27 12:50:10 WARN org.apache.spark.scheduler.FairSchedulableBuilder: Fair Scheduler configuration file not found so jobs will be scheduled in FIFO order. To use fair scheduling, configure pools in fairscheduler.xml or set spark.scheduler.allocation.file to a file that contains the configuration. 20/12/27 12:50:11 INFO org.apache.hadoop.yarn.client.RMProxy: Connecting to ResourceManager at spark-cluster-m/10.142.0.10:8032 20/12/27 12:50:11 INFO org.apache.hadoop.yarn.client.AHSProxy: Connecting to Application History server at spark-cluster-m/10.142.0.10:10200 20/12/27 12:50:13 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl: Submitted application application_1609071162129_0002 Exception in thread "main" java.lang.NoSuchMethodError: org.json4s.jackson.JsonMethods$.parse$default$3()Z at org.apache.spark.sql.execution.datasources.hbase.HBaseTableCatalog$.apply(HBaseTableCatalog.scala:262) at org.apache.spark.sql.execution.datasources.hbase.HBaseRelation.(HBaseRelation.scala:84) at org.apache.spark.sql.execution.datasources.hbase.DefaultSource.createRelation(HBaseRelation.scala:61) at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68) at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127) at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80) at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656) at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77) at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:656) at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267) at com.example.bigtable.spark.shc.BigtableSource$.delayedEndpoint$com$example$bigtable$spark$shc$BigtableSource$1(BigtableSource.scala:56) at com.example.bigtable.spark.shc.BigtableSource$delayedInit$body.apply(BigtableSource.scala:19) at scala.Function0$class.apply$mcV$sp(Function0.scala:34) at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12) at scala.App$$anonfun$main$1.apply(App.scala:76) at scala.App$$anonfun$main$1.apply(App.scala:76) at scala.collection.immutable.List.foreach(List.scala:381) at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35) at scala.App$class.main(App.scala:76) at com.example.bigtable.spark.shc.BigtableSource$.main(BigtableSource.scala:19) at com.example.bigtable.spark.shc.BigtableSource.main(BigtableSource.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:890) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:192) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:217) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 20/12/27 12:50:20 INFO org.spark_project.jetty.server.AbstractConnector: Stopped Spark@3e6cb045{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
ANSWER
Answered 2020-Dec-27 at 13:47Consider reading these related SO questions: 1 and 2.
Under the hood the tutorial you followed, as well of one of the question indicated, use the Apache Spark - Apache HBase Connector provided by HortonWorks.
The problem seems to be related with an incompatibility with the version of the json4s
library: in both cases, it seems that using version 3.2.10
or 3.2.11
in the build process will solve the issue.
QUESTION
I have data such as this, I am trying to use the survey package to apply weights and find the means, SE and the N from each variable.
I was able to find the mean and SE, but I don't know how to pull the N for each variable.
...ANSWER
Answered 2020-Nov-04 at 05:22You don't actually need the survey package functions to do this. The number of observations is whatever it is, it's not a population estimate based on the design. However, the pacakage does have the function unwtd.count
to get unweighted count of non-missing observations, eg
QUESTION
I am new to docker. Hardly I have containerized my php application to run it in the web interface. But I have some cron to run with it. I learnt how to create separate cron image and run it from How to run a cron job inside a docker container?. But my use case is different. I need to use the php files from my php application container which seems not possible from my way. I tried creating the docker-compose.yml as follow to see if it would work
docker-compose.yml:
...ANSWER
Answered 2020-Oct-03 at 13:14I think it's better if you specify the entry point in the docker-compose file without "sh" in front of it. Remember that declaring a new entrypoint in the docker-compose file overwrites the entrypoint in the dockerfile. Link
I would advise you to create your own Entrypoint Script which will execute your crons in the container CMD ["/entrypoint.sh"]
Example:
Create an file and named "entrypoint.sh" or whatever and save it in the same folder where your Dockerfile is located. In this file push your Content from your cron.sh.
QUESTION
How can i achieve below expecting results without using StringEscapeUtils
?
ANSWER
Answered 2020-Aug-26 at 07:26Your regexp is for html tags would be matched byt the html entities will not be matched. Their pattern is something like
&.*?;
Which you are not replacing.
this should solve your trouble:
QUESTION
I have a JSON data that looks like this (link for full response here https://pastebin.com/LG2F9Vrw)
"data": [ { "matchId": 1653309, "personId": 1141434, "teamId": 89736, "competitors": [ { "teamCode": "SHC", "website": "", } ] },
There's an array of ['data']
that I'm using with foreach to give me game statistics. There's now a second array inside of the ['data']
array. I'mn trying to get the ['teamCode']
string to print but I can't work out how to do it.
I've done my best following tutorials online.
...ANSWER
Answered 2020-Aug-15 at 07:51this is simple code how to retreive ['teamCode']
you want (test link):
QUESTION
This is the code I have below, it works just not sure why when it copies over into the second and third column it moves down a row.
...ANSWER
Answered 2020-Jun-11 at 16:06Do not calculate eRow
each time (based on A:A column) when try pasting to the next columns.
Use shB.Paste Destination:=shPM.Cells(eRow , 2)
(not eRow + 1
) for each iteration.
Otherwise, the new added value in column A:A will add another row to eRow
...
Or calculate the last row for each column:
eRow = shPM.Cells(Rows.Count, 2).End(xlUp).Row
and eRow = shPM.Cells(Rows.Count, 3).End(xlUp).Row
, according to the column where you intend to copy the value.
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