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https://issues.apache.org/jira/browse/SEDONA-130?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17572724#comment-17572724
]
Jia Yu commented on SEDONA-130:
-------------------------------
[~imperio] Can you try the examples here?
https://github.com/apache/incubator-sedona/blob/master/examples/viz/src/main/scala/ScalaExample.scala#L104
> Error while testing the Sedona VIZ example
> ------------------------------------------
>
> Key: SEDONA-130
> URL: https://issues.apache.org/jira/browse/SEDONA-130
> Project: Apache Sedona
> Issue Type: Bug
> Reporter: wxmimperio
> Priority: Major
> Attachments: image-2022-06-29-17-52-35-049.png
>
>
> I'm trying to run the Sedona Spark Visualization tutorial code. Example link:
> [https://sedona.apache.org/tutorial/viz/]
> *sedona version: sedona-xxx-3.0_2.12 1.2.0-incubating*
> *spark version: 3.1.3*
> checkin.csv
> {code:java}
> -88.331492,32.324142,hotel
> -88.175933,32.360763,gas
> -88.388954,32.357073,bar
> -88.221102,32.35078,restaurant {code}
> Full test code:
> {code:java}
> describe("visualize") {
> val pointRDDInputLocation = "src/test/doc/checkin.csv"
> val df = sparkSession.read.format("csv").option("header",
> "false").load(pointRDDInputLocation)
> df.createOrReplaceTempView("source")
> df.printSchema()
> df.show() sparkSession.sql(
> """
> CREATE OR REPLACE TEMP VIEW pointtable AS
> |SELECT ST_Point(cast(source._c0 as Decimal(24,20)),cast(source._c1
> as Decimal(24,20))) as shape
> |FROM source
> """.stripMargin
> )
> sparkSession.sql(
> """CREATE OR REPLACE TEMP VIEW boundtable AS
> |SELECT ST_Envelope_Aggr(shape) as bound FROM
> pointtable""".stripMargin
> )
> sparkSession.sql(
> """
> |CREATE OR REPLACE TEMP VIEW pixels AS
> |SELECT pixel, shape FROM pointtable
> |LATERAL VIEW explode(ST_Pixelize(ST_Transform(shape,
> 'epsg:4326','epsg:3857'), 256, 256, (SELECT ST_Transform(bound,
> 'epsg:4326','epsg:3857') FROM boundtable))) AS pixel
> |""".stripMargin
> )
> sparkSession.sql(
> """
> |CREATE OR REPLACE TEMP VIEW pixelaggregates AS
> |SELECT pixel, count(*) as weight
> |FROM pixels
> |GROUP BY pixel
> |""".stripMargin
> )
> sparkSession.sql(
> """
> |CREATE OR REPLACE TEMP VIEW pixelColor AS
> |SELECT pixel, ST_Colorize(weight, (SELECT max(weight) FROM
> pixelaggregates)) as color
> |FROM pixelaggregates
> |""".stripMargin
> )
> sparkSession.sql(
> """
> |CREATE OR REPLACE TEMP VIEW images AS
> |SELECT ST_Render(pixel, color) AS image, (SELECT ST_AsText(bound)
> FROM boundtable) AS boundary
> |FROM pixelColor
> |""".stripMargin
> )
> sparkSession.sql("select * from images").show()
> val image =
> sparkSession.table("images").take(1)(0)(0).asInstanceOf[ImageSerializableWrapper].getImage
> val imageGenerator = new ImageGenerator
> imageGenerator.SaveRasterImageAsLocalFile(image,
> "src/test/doc/output/points", ImageType.PNG)
> } {code}
> Get Error:
> {code:java}
> java.lang.AssertionError: assertion failed
> at scala.Predef$.assert(Predef.scala:204)
> at
> org.apache.spark.sql.sedona_viz.expressions.ST_Render.merge(Render.scala:98)
> at
> org.apache.spark.sql.execution.aggregate.ScalaUDAF.merge(udaf.scala:440)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator$$anonfun$1.$anonfun$applyOrElse$3(AggregationIterator.scala:199)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator$$anonfun$1.$anonfun$applyOrElse$3$adapted(AggregationIterator.scala:199)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator.$anonfun$generateProcessRow$7(AggregationIterator.scala:213)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator.$anonfun$generateProcessRow$7$adapted(AggregationIterator.scala:207)
> at
> org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.processCurrentSortedGroup(SortBasedAggregationIterator.scala:114)
> at
> org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.next(SortBasedAggregationIterator.scala:149)
> at
> org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.next(SortBasedAggregationIterator.scala:30)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:346)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:131)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:498)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:501)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748) {code}
> !image-2022-06-29-17-52-35-049.png!
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