OK looking promising thanks
scala> import scala.util.{Try, Success, Failure}
import scala.util.{Try, Success, Failure}
scala> val df =
Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
"hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
df: org.apache.spark.sql.DataFrame = [brand: string, ocis_party_id: bigint
... 6 more fields]
regards,
Dr Mich Talebzadeh
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such loss, damage or destruction.
On Tue, 5 May 2020 at 23:13, Brandon Geise <brandonge...@gmail.com> wrote:
> Match needs to be lower case “match”
>
>
>
> *From: *Mich Talebzadeh <mich.talebza...@gmail.com>
> *Date: *Tuesday, May 5, 2020 at 6:13 PM
> *To: *Brandon Geise <brandonge...@gmail.com>
> *Cc: *Todd Nist <tsind...@gmail.com>, "user @spark" <user@spark.apache.org
> >
> *Subject: *Re: Exception handling in Spark
>
>
>
>
> scala> import scala.util.{Try, Success, Failure}
>
> import scala.util.{Try, Success, Failure}
>
> scala> val df =
> Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
> "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
> Match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
> <console>:48: error: value Match is not a member of
> scala.util.Try[org.apache.spark.sql.DataFrame]
> val df =
> Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
> "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
> Match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
>
>
>
> Mich Talebzadeh
>
>
>
> LinkedIn
> *https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>*
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
>
>
>
> On Tue, 5 May 2020 at 23:10, Mich Talebzadeh <mich.talebza...@gmail.com>
> wrote:
>
> This is what I get
>
>
>
> scala> val df =
> Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
> "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
> Match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
> <console>:47: error: not found: value Try
> val df =
> Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
> "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
> Match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
> ^
> <console>:47: error: not found: value Success
> val df =
> Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
> "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
> Match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
>
>
> ^
> <console>:47: error: not found: value Failure
> val df =
> Try(spark.read.format("com.databricks.spark.xml").option("rootTag",
> "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml"))
> Match {case Success(df) => df case Failure(e) => throw new Exception("foo")}
>
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn
> *https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>*
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
>
>
>
> On Tue, 5 May 2020 at 23:03, Brandon Geise <brandonge...@gmail.com> wrote:
>
> This is what I had in mind. Can you give this approach a try?
>
>
>
> val df = Try(spark.read.csv("")) match {
>
> case Success(df) => df
>
> case Failure(e) => throw new Exception("foo")
>
> }
>
>
>
> *From: *Mich Talebzadeh <mich.talebza...@gmail.com>
> *Date: *Tuesday, May 5, 2020 at 5:17 PM
> *To: *Todd Nist <tsind...@gmail.com>
> *Cc: *Brandon Geise <brandonge...@gmail.com>, "user @spark" <
> user@spark.apache.org>
> *Subject: *Re: Exception handling in Spark
>
>
>
> I am trying this approach
>
>
>
>
> val broadcastValue = "123456789" // I assume this will be sent as a
> constant for the batch
> // Create a DF on top of XML
> try {
> val df = spark.read.
> format("com.databricks.spark.xml").
> option("rootTag", "hierarchy").
> option("rowTag", "sms_request").
> load("/tmp/broadcast.xml")
> df
> } catch {
> case ex: FileNotFoundException => {
> println (s"\nFile /tmp/broadcast.xml not found\n")
> None
> }
> case unknown: Exception => {
> println(s"\n Error encountered $unknown\n")
> None
> }
> }
>
> val newDF = df.withColumn("broadcastid", lit(broadcastValue))
>
> But this does not work
>
>
>
> scala> try {
> | val df = spark.read.
> | format("com.databricks.spark.xml").
> | option("rootTag", "hierarchy").
> | option("rowTag", "sms_request").
> | load("/tmp/broadcast.xml")
> | Some(df)
> | } catch {
> | case ex: FileNotFoundException => {
> | println (s"\nFile /tmp/broadcast.xml not found\n")
> | None
> | }
> | case unknown: Exception => {
> | println(s"\n Error encountered $unknown\n")
> | None
> | }
> | }
> res6: Option[org.apache.spark.sql.DataFrame] = Some([brand: string,
> ocis_party_id: bigint ... 6 more fields])
>
> scala>
>
> scala> df.printSchema
> <console>:48: error: not found: value df
> df.printSchema
>
> data frame seems to be lost!
>
>
>
> Thanks,
>
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn
> *https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>*
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
>
>
>
> On Tue, 5 May 2020 at 18:08, Mich Talebzadeh <mich.talebza...@gmail.com>
> wrote:
>
> Thanks Todd. This is what I did before creating DF on top of that file
>
>
>
> var exists = true
>
> exists = xmlDirExists(broadcastStagingConfig.xmlFilePath)
>
> if(!exists) {
>
> println(s"\n Error: The xml file ${ broadcastStagingConfig.xmlFilePath}
> does not exist, aborting!\n")
>
> sys.exit(1)
>
> }
>
> .
>
> .
>
> def xmlFileExists(hdfsDirectory: String): Boolean = {
>
> val hadoopConf = new org.apache.hadoop.conf.Configuration()
>
> val fs = org.apache.hadoop.fs.FileSystem.get(hadoopConf)
>
> fs.exists(new org.apache.hadoop.fs.Path(hdfsDirectory))
>
> }
>
>
>
> And checked it. It works.
>
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn
> *https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>*
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
>
>
>
> On Tue, 5 May 2020 at 17:54, Todd Nist <tsind...@gmail.com> wrote:
>
> Could you do something like this prior to calling the action.
>
>
>
> // Create FileSystem object from Hadoop Configuration
>
> val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
>
> // This methods returns Boolean (true - if file exists, false - if file
> doesn't exist
>
> val fileExists = fs.exists(new Path("<parh_to_file>"))
>
> *if* (fileExists) println("File exists!")
>
> *else* println("File doesn't exist!")
>
>
>
> Not sure that will help you or not, just a thought.
>
>
>
> -Todd
>
>
>
>
>
>
>
>
>
> On Tue, May 5, 2020 at 11:45 AM Mich Talebzadeh <mich.talebza...@gmail.com>
> wrote:
>
> Thanks Brandon!
>
>
>
> i should have remembered that.
>
>
>
> basically the code gets out with sys.exit(1) if it cannot find the file
>
>
>
> I guess there is no easy way of validating DF except actioning it by
> show(1,0) etc and checking if it works?
>
>
>
> Regards,
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn
> *https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>*
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
>
>
>
> On Tue, 5 May 2020 at 16:41, Brandon Geise <brandonge...@gmail.com> wrote:
>
> You could use the Hadoop API and check if the file exists.
>
>
>
> *From: *Mich Talebzadeh <mich.talebza...@gmail.com>
> *Date: *Tuesday, May 5, 2020 at 11:25 AM
> *To: *"user @spark" <user@spark.apache.org>
> *Subject: *Exception handling in Spark
>
>
>
> Hi,
>
>
>
> As I understand exception handling in Spark only makes sense if one
> attempts an action as opposed to lazy transformations?
>
>
>
> Let us assume that I am reading an XML file from the HDFS directory and
> create a dataframe DF on it
>
>
>
> val broadcastValue = "123456789" // I assume this will be sent as a
> constant for the batch
>
> // Create a DF on top of XML
> val df = spark.read.
> format("com.databricks.spark.xml").
> option("rootTag", "hierarchy").
> option("rowTag", "sms_request").
> load("/tmp/broadcast.xml")
>
> val newDF = df.withColumn("broadcastid", lit(broadcastValue))
>
> newDF.createOrReplaceTempView("tmp")
>
> // Put data in Hive table
> //
> sqltext = """
> INSERT INTO TABLE michtest.BroadcastStaging PARTITION
> (broadcastid="123456", brand)
> SELECT
> ocis_party_id AS partyId
> , target_mobile_no AS phoneNumber
> , brand
> , broadcastid
> FROM tmp
> """
> //
>
> // Here I am performing a collection
>
> try {
>
> spark.sql(sqltext)
>
> } catch {
>
> case e: SQLException => e.printStackTrace
>
> sys.exit()
>
> }
>
>
>
> Now the issue I have is that what if the xml file /tmp/broadcast.xml does
> not exist or deleted? I won't be able to catch the error until the hive
> table is populated. Of course I can write a shell script to check if the
> file exist before running the job or put small collection like
> df.show(1,0). Are there more general alternatives?
>
>
>
> Thanks
>
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn
> *https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>*
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
