soumilshah1995 commented on issue #8019:
URL: https://github.com/apache/hudi/issues/8019#issuecomment-1440395879
Hi @papablus
i tried show_commit and im getting following error can you please tell me if
there is something i am not doing right
```
try:
import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql.session import SparkSession
from awsglue.dynamicframe import DynamicFrame
from pyspark.sql.functions import col, to_timestamp,
monotonically_increasing_id, to_date, when
from pyspark.sql.functions import *
from awsglue.utils import getResolvedOptions
from awsglueml.transforms import EntityDetector
from pyspark.sql.types import StringType
from pyspark.sql.types import *
from datetime import datetime
import boto3
from functools import reduce
except Exception as e:
print("Error ")
spark = (SparkSession.builder
.config('spark.serializer',
'org.apache.spark.serializer.KryoSerializer')
.config('spark.sql.hive.convertMetastoreParquet', 'false')
.config('spark.sql.catalog.spark_catalog',
'org.apache.spark.sql.hudi.catalog.HoodieCatalog')
.config('spark.sql.extensions',
'org.apache.spark.sql.hudi.HoodieSparkSessionExtension')
.config('spark.sql.legacy.pathOptionBehavior.enabled',
'true').getOrCreate())
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
logger = glueContext.get_logger()
db_name = "hudidb"
table_name = "hudi_table"
recordkey = 'emp_id'
path = "s3://hudi-demos-emr-serverless-project-soumil/tmp/"
method = 'upsert'
table_type = "COPY_ON_WRITE"
precombine = "ts"
partiton_field = "date"
connection_options = {
"path": path,
"connectionName": "hudi-connection",
"hoodie.datasource.write.storage.type": table_type,
'hoodie.datasource.write.precombine.field': precombine,
'className': 'org.apache.hudi',
'hoodie.table.name': table_name,
'hoodie.datasource.write.recordkey.field': recordkey,
'hoodie.datasource.write.table.name': table_name,
'hoodie.datasource.write.operation': method,
'hoodie.datasource.hive_sync.enable': 'true',
"hoodie.datasource.hive_sync.mode": "hms",
'hoodie.datasource.hive_sync.sync_as_datasource': 'false',
'hoodie.datasource.hive_sync.database': db_name,
'hoodie.datasource.hive_sync.table': table_name,
'hoodie.datasource.hive_sync.use_jdbc': 'false',
'hoodie.datasource.hive_sync.partition_extractor_class':
'org.apache.hudi.hive.MultiPartKeysValueExtractor',
'hoodie.datasource.write.hive_style_partitioning': 'true',
}
df = spark. \
read. \
format("hudi"). \
load(path)
print("\n")
print(df.show(2))
print("\n")
try:
varSP = spark.sql("call show_commits('hudidb.hudi_table', 10)")
print(varSP.show())
except Exception as e:
print("Error 1", e)
try:
varSP = spark.sql("call show_commits('hudidb.hudi_table', '10')")
print(varSP.show())
except Exception as e:
print("Error 2", e)
```
### Error Message
```
<html>
<body>
<!--StartFragment-->
An error occurred while calling o90.sql.: java.lang.AssertionError:
assertion failed: It's not a Hudi table at
scala.Predef$.assert(Predef.scala:219) at
org.apache.spark.sql.catalyst.catalog.HoodieCatalogTable.<init>(HoodieCatalogTable.scala:51)
at
org.apache.spark.sql.catalyst.catalog.HoodieCatalogTable$.apply(HoodieCatalogTable.scala:367)
at
org.apache.spark.sql.catalyst.catalog.HoodieCatalogTable$.apply(HoodieCatalogTable.scala:363)
at
org.apache.hudi.HoodieCLIUtils$.getHoodieCatalogTable(HoodieCLIUtils.scala:70)
at
org.apache.spark.sql.hudi.command.procedures.ShowCommitsProcedure.call(ShowCommitsProcedure.scala:82)
at
org.apache.spark.sql.hudi.command.CallProcedureHoodieCommand.run(CallProcedureHoodieCommand.scala:33)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:75)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:73)
at org.apache.spark.sql.execution.command.ExecutedComman
dExec.executeColle
--
ct(commands.scala:84) at
org.apache.spark.sql.execution.QueryExecution$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:103)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at
org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:224)
at
org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:114)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$7(SQLExecution.scala:139)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at
org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:224)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:139)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:245)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.
scala:138) at org
.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68)
at
org.apache.spark.sql.execution.QueryExecution$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:100)
at
org.apache.spark.sql.execution.QueryExecution$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:96)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:615)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:177)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:615)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$super$transformDownWithPruning(LogicalPlan.scala:30)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.p
lans.logical.Anal
ysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:591)
at
org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:96)
at
org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:83)
at
org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:81)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:222) at
org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:102) at
org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at
org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:99) at
org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:622) at
org.apache.sp
ark.sql.SparkSess
ion.withActive(SparkSession.scala:779) at
org.apache.spark.sql.SparkSession.sql(SparkSession.scala:617) 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
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 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.lang.Thread.run(Thread.java:750)
<!--EndFragment-->
</body>
</html>
```
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