rychu151 opened a new issue, #10222:
URL: https://github.com/apache/iceberg/issues/10222
### Query engine
Spark
### Question
Im trying to setup local develop env for my testing purposes using docker
**Target is to save dataframe in a Iceberg format and Hive-metadata**
Here is my current docker-compose:
```
version: "3"
services:
#Jupyter Notebook with PySpark & iceberg Server
spark-iceberg:
image: tabulario/spark-iceberg
container_name: spark-iceberg
build: spark/
networks:
iceberg_net:
depends_on:
#- rest
- minio
volumes:
- ./warehouse:/home/iceberg/warehouse
- ./notebooks:/home/iceberg/notebooks/notebooks
-
./spark-iceberg/spark/jars/nessie-spark-extensions-3.5_2.12-0.80.0.jar:/opt/spark/jars/nessie-spark-extensions-3.5_2.12-0.80.0.jar
-
./spark-iceberg/spark/conf/spark-defaults.conf:/opt/spark/conf/spark-defaults.conf
environment:
- AWS_ACCESS_KEY_ID=admin
- AWS_SECRET_ACCESS_KEY=password
- AWS_REGION=us-east-1
- USE_STREAM_CAPABLE_STATE_STORE=true
- CATALOG_WAREHOUSE=s3://warehouse/
ports:
- "8888:8888"
- "8080:8080"
- "10000:10000"
- "10001:10001"
# Minio Storage Server
minio:
image: bitnami/minio:latest # not miniop/minio because of reported
issues with the image
container_name: minio
environment:
- MINIO_ROOT_USER=admin
- MINIO_ROOT_PASSWORD=password
- MINIO_REGION=us-east-1
- MINIO_REGION_NAME=us-east-1
networks:
iceberg_net:
aliases:
- warehouse.minio
ports:
- "9001:9001"
- "9000:9000"
#hive metastore
hive-metastore:
image: apache/hive:4.0.0
container_name: hive-metastore
networks:
iceberg_net:
ports:
- "9083:9083"
environment:
- SERVICE_NAME=metastore
depends_on:
- zookeeper
- postgres
volumes:
- ./hive_metastore/conf/hive-site.xml:/opt/hive/conf/hive-site.xml
```
spark-defaults.conf:
```
spark.sql.extensions
org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions
spark.sql.catalog.hive_prod org.apache.iceberg.spark.SparkCatalog
spark.sql.catalog.hive_prod.type hive
spark.sql.catalog.hive_prod.uri thrift://hive-metastore:9083
spark.sql.catalog.hive_prod.io-impl
org.apache.iceberg.aws.s3.S3FileIO
spark.sql.catalog.hive_prod.s3.endpoint http://minio:9000
spark.sql.catalog.hive_prod.warehouse s3://warehouse/
hive.metastore.uris thrift://hive-metastore:9083
```
and hive-site.xml
```
<configuration>
<property>
<name>hive.server2.enable.doAs</name>
<value>false</value>
</property>
<property>
<name>hive.tez.exec.inplace.progress</name>
<value>false</value>
</property>
<property>
<name>hive.exec.scratchdir</name>
<value>/opt/hive/scratch_dir</value>
</property>
<property>
<name>hive.user.install.directory</name>
<value>/opt/hive/install_dir</value>
</property>
<property>
<name>tez.runtime.optimize.local.fetch</name>
<value>true</value>
</property>
<property>
<name>hive.exec.submit.local.task.via.child</name>
<value>false</value>
</property>
<property>
<name>mapreduce.framework.name</name>
<value>local</value>
</property>
<property>
<name>tez.local.mode</name>
<value>true</value>
</property>
<property>
<name>hive.execution.engine</name>
<value>tez</value>
</property>
<property>
<name>metastore.metastore.event.db.notification.api.auth</name>
<value>false</value>
</property>
<property>
<name>hive.metastore.warehouse.dir</name>
<value>s3a://warehouse/</value>
</property>
<property>
<name>fs.s3a.endpoint</name>
<value>http://localhost:9000</value>
</property>
<property>
<name>fs.s3a.access.key</name>
<value>admin</value>
</property>
<property>
<name>fs.s3a.secret.key</name>
<value>password</value>
</property>
<property>
<name>fs.s3a.path.style.access</name>
<value>true</value>
</property>
<property>
<name>fs.s3a.impl</name>
<value>org.apache.hadoop.fs.s3a.S3AFileSystem</value>
</property>
<property>
<name>fs.s3a.connection.ssl.enabled</name>
<value>false</value>
</property>
<property>
<name>hive.metastore.authorization.storage.checks</name>
<value>false</value>
<description>Disables storage-based authorization checks to allow
Hive better compatibility with MinIO.
</description>
</property>
</configuration>
```
using MinIO US i have created a bucket called `warehouse` and set it to
public access
**Target is to save dataframe in a Iceberg format and Hive-metadata** so i
will be able to browse this data using Apache Druid
in order to create a table i use PySpark:
```
col_name = "col_name"
label_name = "label"
data_name = "upload_date"
schema = StructType([
StructField(data_name, LongType(), False),
StructField(col_name, StringType(), False),
StructField(label_name, StringType(), False)
])
spark =
SparkSession.builder.appName("schema_example").enableHiveSupport().getOrCreate()
spark.conf.set("spark.sql.iceberg.catalog.hive_prod", "DEBUG")
spark.conf.set("spark.hadoop.fs.s3a.aws.credentials.provider",
"org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider")
data = []
df = spark.createDataFrame(data, schema)
```
spark.sql("SHOW DATABASES ").show()
prints only `default` database
when i try to create a database like below:
`spark.sql('CREATE DATABASE IF NOT EXISTS hive_prod.testing')`
i get the following error:
```
Py4JJavaError: An error occurred while calling o34.sql.
: java.lang.RuntimeException: Failed to create namespace testing in Hive
Metastore
at org.apache.iceberg.hive.HiveCatalog.createNamespace(HiveCatalog.java:299)
Caused by: MetaException(message:Failed to create external path
s3://warehouse/testing.db for database testing. This may result in access not
being allowed if the StorageBasedAuthorizationProvider is enabled: null)
```
anyone understands why?
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