Shantanu0701 opened a new issue, #10364:
URL: https://github.com/apache/iceberg/issues/10364
As I have created a view as seen below but when I am printing its showing
error. So can't even say if the views are created successfully or not.
import pyspark
from pyspark.sql import SparkSession
import os
# Initialize SparkConf with necessary configurations
conf = (
pyspark.SparkConf()
.setAppName('app_name') # Set the application name for Spark
# Specify the Iceberg package to be used
.set('spark.jars.packages',
'org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.5.1')
# Add Iceberg SQL Extensions to enable Iceberg-specific SQL
operations
.set('spark.sql.extensions',
'org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions')
# Configure the Iceberg catalog
.set('spark.sql.catalog.localcat',
'org.apache.iceberg.spark.SparkCatalog') # Define the catalog implementation
.set('spark.sql.catalog.localcat.type', 'hadoop') # Set the catalog
type to Hadoop
.set('spark.sql.catalog.localcat.warehouse',
'/home/user/Downloads/first_task/warehouse') # Specify the warehouse directory
.set('spark.sql.catalog.localcat2',
'org.apache.iceberg.spark.SparkCatalog') # Define the catalog implementation
.set('spark.sql.catalog.localcat2.type', 'hadoop') # Set the catalog
type to Hadoop
.set('spark.sql.catalog.localcat2.warehouse',
'/home/user/Downloads/first_task/warehouse2')
)
# Create a SparkSession with the previously defined configurations
spark = SparkSession.builder.config(conf=conf).getOrCreate()
print("Spark Running")
# Create a table named 'first_table' in the 'localcat.localdb' catalog using
Iceberg format
spark.sql("CREATE TABLE localcat.localdb.first_table (id bigint, first_name
string, last_name string ) USING iceberg")
spark.sql("CREATE TABLE localcat2.localdb3.demo1 (id bigint, first_name
string, last_name string) USING iceberg")
# Insert data into the 'first_table'
spark.sql("INSERT INTO localcat2.localdb3.demo1 VALUES (1,'Alex',
'Merced'),(2,'Demon', 'Merced'),(3,'Lord', '')")
spark.sql("INSERT INTO localcat.localdb.first_table VALUES (1,'Alex',
'Merced'),(2,'Demon', 'Merced'),(3,'Lord', '')")
# Query the table to display all records
spark.sql("SELECT * FROM localcat.localdb.first_table").show()
spark.sql("SELECT * FROM localcat.localdb.first_table.history").show()
spark.sql("CREATE VIEW filtered_view AS SELECT * FROM
localcat.localdb.first_table WHERE id > 1")
spark.sql("SHOW VIEWS").show()
Getting below error:
spark.sql("SHOW VIEWS").show()
py4j.protocol.Py4JJavaError: An error occurred while calling o43.sql.
: java.lang.AssertionError: assertion failed
at scala.Predef$.assert(Predef.scala:208)
at
org.apache.spark.sql.connector.catalog.LookupCatalog$CatalogAndNamespace$.unapply(LookupCatalog.scala:84)
at
org.apache.spark.sql.catalyst.analysis.RewriteViewCommands$$anonfun$apply$1.applyOrElse(RewriteViewCommands.scala:74)
at
org.apache.spark.sql.catalyst.analysis.RewriteViewCommands$$anonfun$apply$1.applyOrElse(RewriteViewCommands.scala:51)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUpWithPruning$3(AnalysisHelper.scala:138)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(origin.scala:76)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUpWithPruning$1(AnalysisHelper.scala:138)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:323)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUpWithPruning(AnalysisHelper.scala:134)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUpWithPruning$(AnalysisHelper.scala:130)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUpWithPruning(LogicalPlan.scala:32)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUp(AnalysisHelper.scala:111)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUp$(AnalysisHelper.scala:110)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUp(LogicalPlan.scala:32)
at
org.apache.spark.sql.catalyst.analysis.RewriteViewCommands.apply(RewriteViewCommands.scala:51)
at
org.apache.spark.sql.catalyst.parser.extensions.IcebergSparkSqlExtensionsParser.parsePlan(IcebergSparkSqlExtensionsParser.scala:126)
at
org.apache.spark.sql.SparkSession.$anonfun$sql$2(SparkSession.scala:631)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:138)
at
org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:630)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:629)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:659)
at
java.base/jdk.internal.reflect.DirectMethodHandleAccessor.invoke(DirectMethodHandleAccessor.java:103)
at java.base/java.lang.reflect.Method.invoke(Method.java:580)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at
py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.base/java.lang.Thread.run(Thread.java:1570)
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