End to End xtable to Trino query with source iceberg and target hudi and Delta Lake with HMS and S3 #463

alberttwong · 2024-06-07T18:39:19Z

alberttwong
Jun 7, 2024

Using openjdk 11, spark 3.4, hive 2.3.10, hadoop 2.10.2

using https://github.com/alberttwong/incubator-xtable/tree/main/demo-s3 as the base

alberttwong · 2024-06-07T18:39:25Z

alberttwong
Jun 7, 2024
Author

spark-sql --packages org.apache.iceberg:iceberg-spark-runtime-3.4_2.12:1.5.2,org.apache.iceberg:iceberg-aws-bundle:1.5.2,org.apache.hadoop:hadoop-client:2.10.2,com.amazonaws:aws-java-sdk-s3:1.11.271,org.apache.hadoop:hadoop-aws:2.10.2 \
    --conf spark.hadoop.fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider \
    --conf spark.sql.defaultCatalog=iceberg \
    --conf spark.sql.catalog.iceberg=org.apache.iceberg.spark.SparkCatalog \
    --conf spark.sql.catalog.iceberg.warehouse=s3://warehouse \
    --conf spark.sql.catalog.iceberg.type=hive

0 replies

alberttwong · 2024-06-07T19:01:45Z

alberttwong
Jun 7, 2024
Author

spark-sql ()> CREATE TABLE iceberg_db.taxis 
            > (
            >   vendor_id bigint,
            >   trip_id bigint,
            >   trip_distance float,
            >   fare_amount double,
            >   store_and_fwd_flag string
            > )
            > PARTITIONED BY (vendor_id) ;
24/06/07 19:01:16 ERROR SparkSQLDriver: Failed in [CREATE TABLE iceberg_db.taxis 
(
  vendor_id bigint,
  trip_id bigint,
  trip_distance float,
  fare_amount double,
  store_and_fwd_flag string
)
PARTITIONED BY (vendor_id) ]
software.amazon.awssdk.services.s3.model.S3Exception: The bucket you are attempting to access must be addressed using the specified endpoint. Please send all future requests to this endpoint. (Service: S3, Status Code: 301, Request ID: E0FK57YQCA0RDX2A, Extended Request ID: bS92IKcb8KbhjrzTBBee08q2kkiNg2cYp+jOX6RldUZ8BrEhFwDz0GoU7LzRwnMRZ1HBvUinByM=)

1 reply

alberttwong Jun 7, 2024
Author

don't use --conf spark.sql.catalog.iceberg.io-impl=org.apache.iceberg.aws.s3.S3FileIO. used a different spark-sql command

alberttwong · 2024-06-07T19:49:45Z

alberttwong
Jun 7, 2024
Author

CREATE SCHEMA iceberg_db LOCATION 's3a://warehouse/';
CREATE TABLE iceberg_db.taxis 
(
  vendor_id bigint,
  trip_id bigint,
  trip_distance float,
  fare_amount double,
  store_and_fwd_flag string
)
PARTITIONED BY (vendor_id) ;
INSERT INTO iceberg_db.taxis VALUES (1, 1000371, 1.8, 15.32, 'N'), (2, 1000372, 2.5, 22.15, 'N'), (2, 1000373, 0.9, 9.01, 'N'), (1, 1000374, 8.4, 42.13, 'Y');

0 replies

alberttwong · 2024-06-07T19:56:43Z

alberttwong
Jun 7, 2024
Author

Trino shows the data.

sh-5.1$ trino
trino> select * from iceberg.iceberg_db.taxis;
 vendor_id | trip_id | trip_distance | fare_amount | store_and_fwd_flag 
-----------+---------+---------------+-------------+--------------------
         1 | 1000371 |           1.8 |       15.32 | N                  
         1 | 1000374 |           8.4 |       42.13 | Y                  
         2 | 1000372 |           2.5 |       22.15 | N                  
         2 | 1000373 |           0.9 |        9.01 | N                  
(4 rows)

Query 20240607_200019_00001_ynf4i, FINISHED, 1 node
Splits: 2 total, 2 done (100.00%)
0.29 [4 rows, 3KB] [13 rows/s, 10.4KB/s]

spark-sql shows the data

spark-sql ()> use iceberg_db;
Time taken: 0.091 seconds
spark-sql (iceberg_db)> show tables;
taxis
Time taken: 0.253 seconds, Fetched 1 row(s)
spark-sql (iceberg_db)> select * from taxis;
1       1000371 1.8     15.32   N
1       1000374 8.4     42.13   Y
2       1000372 2.5     22.15   N
2       1000373 0.9     9.01    N

files in s3 show correctly

sh-5.1# mc alias set warehouse http://minio:9000 admin password
Added `warehouse` successfully.
sh-5.1# mc ls -r warehouse
[2024-06-07 20:01:59 UTC]     0B STANDARD warehouse/taxis/_delta_log/
[2024-06-07 20:00:59 UTC] 1.5KiB STANDARD warehouse/taxis/data/vendor_id=1/00000-10-e0fc3ef1-3606-4591-bcf6-d72b25747380-0-00001.parquet
[2024-06-07 19:59:51 UTC] 1.5KiB STANDARD warehouse/taxis/data/vendor_id=1/00000-5-865f6992-e612-49a0-a8db-a27fd0f7d02a-0-00001.parquet
[2024-06-07 20:00:59 UTC] 1.5KiB STANDARD warehouse/taxis/data/vendor_id=2/00000-10-e0fc3ef1-3606-4591-bcf6-d72b25747380-0-00002.parquet
[2024-06-07 19:59:51 UTC] 1.5KiB STANDARD warehouse/taxis/data/vendor_id=2/00000-5-865f6992-e612-49a0-a8db-a27fd0f7d02a-0-00002.parquet
[2024-06-07 19:59:24 UTC] 1.4KiB STANDARD warehouse/taxis/metadata/00000-77bdf818-507f-48f1-971a-1898c294bf49.metadata.json
[2024-06-07 19:59:51 UTC] 2.4KiB STANDARD warehouse/taxis/metadata/00001-ef7e1726-2ec0-4582-bef8-9c37f96e2909.metadata.json
[2024-06-07 20:00:59 UTC] 3.4KiB STANDARD warehouse/taxis/metadata/00002-15d50d43-f5d8-4faa-b2b7-f41aca3f758f.metadata.json
[2024-06-07 19:59:51 UTC] 7.0KiB STANDARD warehouse/taxis/metadata/ae7384d8-6b4a-4fd6-bbc2-e9b621ba9e0b-m0.avro
[2024-06-07 20:00:59 UTC] 7.0KiB STANDARD warehouse/taxis/metadata/ebef7e50-73aa-4428-98aa-6ad0a8ed7802-m0.avro
[2024-06-07 19:59:51 UTC] 4.1KiB STANDARD warehouse/taxis/metadata/snap-1202211864160811787-1-ae7384d8-6b4a-4fd6-bbc2-e9b621ba9e0b.avro
[2024-06-07 20:00:59 UTC] 4.2KiB STANDARD warehouse/taxis/metadata/snap-3391991307049980362-1-ebef7e50-73aa-4428-98aa-6ad0a8ed7802.avro

root@spark:/opt/xtable/jars# export AWS_SECRET_ACCESS_KEY=password
root@spark:/opt/xtable/jars# export AWS_ACCESS_KEY_ID=admin
root@spark:/opt/xtable/jars# export ENDPOINT=http://minio:9000
root@spark:/opt/xtable/jars# export AWS_REGION=us-east-1
root@spark:/opt/xtable/jars# cd /opt/xtable/jars/; java -jar xtable-utilities-0.1.0-SNAPSHOT-bundled.jar --datasetConfig xtable_iceberg.yaml -p core-site.xml
WARNING: Runtime environment or build system does not support multi-release JARs. This will impact location-based features.
2024-06-07 19:54:51 INFO  org.apache.xtable.utilities.RunSync:148 - Running sync for basePath s3a://warehouse/taxis for following table formats [HUDI, DELTA]
2024-06-07 19:54:51 INFO  org.apache.hudi.common.table.HoodieTableMetaClient:133 - Loading HoodieTableMetaClient from s3a://warehouse/taxis
2024-06-07 19:54:51 WARN  org.apache.hadoop.util.NativeCodeLoader:60 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2024-06-07 19:54:51 WARN  org.apache.hadoop.metrics2.impl.MetricsConfig:136 - Cannot locate configuration: tried hadoop-metrics2-s3a-file-system.properties,hadoop-metrics2.properties
2024-06-07 19:54:52 WARN  org.apache.hadoop.fs.s3a.SDKV2Upgrade:39 - Directly referencing AWS SDK V1 credential provider com.amazonaws.auth.DefaultAWSCredentialsProviderChain. AWS SDK V1 credential providers will be removed once S3A is upgraded to SDK V2
2024-06-07 19:54:52 INFO  org.apache.xtable.hudi.HudiTableManager:73 - Hudi table does not exist, will be created on first sync
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/opt/xtable/jars/xtable-utilities-0.1.0-SNAPSHOT-bundled.jar) to constructor java.nio.DirectByteBuffer(long,int)
WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
2024-06-07 19:54:53 INFO  org.apache.spark.sql.delta.storage.DelegatingLogStore:60 - LogStore `LogStoreAdapter(io.delta.storage.S3SingleDriverLogStore)` is used for scheme `s3a`
2024-06-07 19:54:53 INFO  org.apache.spark.sql.delta.DeltaLog:60 - Creating initial snapshot without metadata, because the directory is empty
2024-06-07 19:54:54 INFO  org.apache.spark.sql.delta.InitialSnapshot:60 - [tableId=95c3e958-7fec-4917-bb9d-28bdf4504d33] Created snapshot InitialSnapshot(path=s3a://warehouse/taxis/_delta_log, version=-1, metadata=Metadata(bd69b4e8-e7de-4df2-b8fe-6ada0e1d0cc8,null,null,Format(parquet,Map()),null,List(),Map(),Some(1717790094004)), logSegment=LogSegment(s3a://warehouse/taxis/_delta_log,-1,List(),None,-1), checksumOpt=None)
2024-06-07 19:54:54 INFO  org.apache.xtable.conversion.ConversionController:240 - No previous InternalTable sync for target. Falling back to snapshot sync.
2024-06-07 19:54:54 INFO  org.apache.xtable.conversion.ConversionController:240 - No previous InternalTable sync for target. Falling back to snapshot sync.
2024-06-07 19:54:54 WARN  org.apache.iceberg.hadoop.HadoopTableOperations:325 - Error reading version hint file s3a://warehouse/taxis/metadata/version-hint.text
java.io.FileNotFoundException: No such file or directory: s3a://warehouse/taxis/metadata/version-hint.text
        at org.apache.hadoop.fs.s3a.S3AFileSystem.s3GetFileStatus(S3AFileSystem.java:3801) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.s3a.S3AFileSystem.innerGetFileStatus(S3AFileSystem.java:3652) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.s3a.S3AFileSystem.extractOrFetchSimpleFileStatus(S3AFileSystem.java:5288) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.s3a.S3AFileSystem.lambda$executeOpen$6(S3AFileSystem.java:1578) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.statistics.impl.IOStatisticsBinding.invokeTrackingDuration(IOStatisticsBinding.java:547) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.statistics.impl.IOStatisticsBinding.lambda$trackDurationOfOperation$5(IOStatisticsBinding.java:528) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.statistics.impl.IOStatisticsBinding.trackDuration(IOStatisticsBinding.java:449) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.s3a.S3AFileSystem.executeOpen(S3AFileSystem.java:1576) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.s3a.S3AFileSystem.open(S3AFileSystem.java:1550) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:997) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.iceberg.hadoop.HadoopTableOperations.findVersion(HadoopTableOperations.java:318) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.iceberg.hadoop.HadoopTableOperations.refresh(HadoopTableOperations.java:104) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.iceberg.hadoop.HadoopTableOperations.current(HadoopTableOperations.java:84) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.iceberg.hadoop.HadoopTables.load(HadoopTables.java:94) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergTableManager.lambda$getTable$1(IcebergTableManager.java:58) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at java.util.Optional.orElseGet(Unknown Source) [?:?]
        at org.apache.xtable.iceberg.IcebergTableManager.getTable(IcebergTableManager.java:58) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergConversionSource.initSourceTable(IcebergConversionSource.java:81) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergConversionSource.getSourceTable(IcebergConversionSource.java:60) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergConversionSource.getCurrentSnapshot(IcebergConversionSource.java:121) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.spi.extractor.ExtractFromSource.extractSnapshot(ExtractFromSource.java:38) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.conversion.ConversionController.syncSnapshot(ConversionController.java:183) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.conversion.ConversionController.sync(ConversionController.java:121) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.utilities.RunSync.main(RunSync.java:169) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
2024-06-07 19:54:54 ERROR org.apache.xtable.utilities.RunSync:171 - Error running sync for s3a://warehouse/taxis
org.apache.iceberg.exceptions.NoSuchTableException: Table does not exist at location: s3a://warehouse/taxis
        at org.apache.iceberg.hadoop.HadoopTables.load(HadoopTables.java:97) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergTableManager.lambda$getTable$1(IcebergTableManager.java:58) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at java.util.Optional.orElseGet(Unknown Source) ~[?:?]
        at org.apache.xtable.iceberg.IcebergTableManager.getTable(IcebergTableManager.java:58) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergConversionSource.initSourceTable(IcebergConversionSource.java:81) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergConversionSource.getSourceTable(IcebergConversionSource.java:60) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.iceberg.IcebergConversionSource.getCurrentSnapshot(IcebergConversionSource.java:121) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.spi.extractor.ExtractFromSource.extractSnapshot(ExtractFromSource.java:38) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.conversion.ConversionController.syncSnapshot(ConversionController.java:183) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.conversion.ConversionController.sync(ConversionController.java:121) ~[xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]
        at org.apache.xtable.utilities.RunSync.main(RunSync.java:169) [xtable-utilities-0.1.0-SNAPSHOT-bundled.jar:0.1.0-SNAPSHOT]

1 reply

alberttwong Jun 7, 2024
Author

hint? #431 (comment). switching to hadoop type

alberttwong · 2024-06-07T20:51:39Z

alberttwong
Jun 7, 2024
Author

    spark-sql --packages org.apache.iceberg:iceberg-spark-runtime-3.4_2.12:1.5.2,org.apache.iceberg:iceberg-aws-bundle:1.5.2,org.apache.hadoop:hadoop-client:2.10.2,com.amazonaws:aws-java-sdk-s3:1.11.271,org.apache.hadoop:hadoop-aws:2.10.2 \
    --conf spark.hadoop.fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider \
    --conf spark.sql.defaultCatalog=iceberg \
    --conf spark.sql.catalog.iceberg=org.apache.iceberg.spark.SparkCatalog \
    --conf spark.sql.catalog.iceberg.warehouse=s3://warehouse \
    --conf spark.sql.catalog.iceberg.type=hadoop

error

Exception in thread "main" org.apache.iceberg.exceptions.RuntimeIOException: Failed to get file system for path: s3://warehouse
        at org.apache.iceberg.hadoop.Util.getFs(Util.java:58)
        at org.apache.iceberg.hadoop.HadoopCatalog.initialize(HadoopCatalog.java:112)
        at org.apache.iceberg.CatalogUtil.loadCatalog(CatalogUtil.java:255)
        at org.apache.iceberg.CatalogUtil.buildIcebergCatalog(CatalogUtil.java:309)
        at org.apache.iceberg.spark.SparkCatalog.buildIcebergCatalog(SparkCatalog.java:154)
        at org.apache.iceberg.spark.SparkCatalog.initialize(SparkCatalog.java:751)
        at org.apache.spark.sql.connector.catalog.Catalogs$.load(Catalogs.scala:65)
        at org.apache.spark.sql.connector.catalog.CatalogManager.$anonfun$catalog$1(CatalogManager.scala:53)
        at scala.collection.mutable.HashMap.getOrElseUpdate(HashMap.scala:86)
        at org.apache.spark.sql.connector.catalog.CatalogManager.catalog(CatalogManager.scala:53)
        at org.apache.spark.sql.connector.catalog.CatalogManager.currentCatalog(CatalogManager.scala:122)
        at org.apache.spark.sql.connector.catalog.CatalogManager.currentNamespace(CatalogManager.scala:93)
        at org.apache.spark.sql.internal.CatalogImpl.currentDatabase(CatalogImpl.scala:65)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.currentDB$1(SparkSQLCLIDriver.scala:285)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.promptWithCurrentDB$1(SparkSQLCLIDriver.scala:292)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:296)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.base/java.lang.reflect.Method.invoke(Unknown Source)
        at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
        at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:1020)
        at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:192)
        at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:215)
        at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:91)
        at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1111)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1120)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.hadoop.fs.UnsupportedFileSystemException: No FileSystem for scheme "s3"
        at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3443)
        at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3466)
        at org.apache.hadoop.fs.FileSystem.access$300(FileSystem.java:174)
        at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3574)
        at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3521)
        at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:540)
        at org.apache.hadoop.fs.Path.getFileSystem(Path.java:365)
        at org.apache.iceberg.hadoop.Util.getFs(Util.java:56)

1 reply

alberttwong Jun 7, 2024
Author

have to use s3a

    spark-sql --packages org.apache.iceberg:iceberg-spark-runtime-3.4_2.12:1.5.2,org.apache.iceberg:iceberg-aws-bundle:1.5.2,org.apache.hadoop:hadoop-client:2.10.2,com.amazonaws:aws-java-sdk-s3:1.11.271,org.apache.hadoop:hadoop-aws:2.10.2 \
    --conf spark.hadoop.fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider \
    --conf spark.sql.defaultCatalog=iceberg \
    --conf spark.sql.catalog.iceberg=org.apache.iceberg.spark.SparkCatalog \
    --conf spark.sql.catalog.iceberg.warehouse=s3a://warehouse \
    --conf spark.sql.catalog.iceberg.type=hadoop

alberttwong · 2024-06-07T21:06:51Z

alberttwong
Jun 7, 2024
Author

spark-sql ()> show schemas;
24/06/07 21:06:27 ERROR SparkSQLDriver: Failed in [show schemas]
java.lang.IllegalArgumentException: path must be absolute
        at com.google.common.base.Preconditions.checkArgument(Preconditions.java:92)
        at org.apache.hadoop.fs.s3a.s3guard.PathMetadata.<init>(PathMetadata.java:68)
        at org.apache.hadoop.fs.s3a.s3guard.PathMetadata.<init>(PathMetadata.java:60)
        at org.apache.hadoop.fs.s3a.s3guard.PathMetadata.<init>(PathMetadata.java:56)
        at org.apache.hadoop.fs.s3a.s3guard.S3Guard.putAndReturn(S3Guard.java:147)
        at org.apache.hadoop.fs.s3a.S3AFileSystem.innerGetFileStatus(S3AFileSystem.java:1876)
        at org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1812)
        at org.apache.iceberg.hadoop.HadoopCatalog.isDirectory(HadoopCatalog.java:176)
        at org.apache.iceberg.hadoop.HadoopCatalog.isNamespace(HadoopCatalog.java:377)
        at org.apache.iceberg.hadoop.HadoopCatalog.listNamespaces(HadoopCatalog.java:307)
        at org.apache.iceberg.catalog.SupportsNamespaces.listNamespaces(SupportsNamespaces.java:74)
        at org.apache.iceberg.spark.SparkCatalog.listNamespaces(SparkCatalog.java:434)
        at org.apache.spark.sql.execution.datasources.v2.ShowNamespacesExec.run(ShowNamespacesExec.scala:42)
        at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result$lzycompute(V2CommandExec.scala:43)
        at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result(V2CommandExec.scala:43)
        at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.executeCollect(V2CommandExec.scala:49)
        at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)
        at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)
        at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)
        at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
        at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
        at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)
        at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
        at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
        at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
        at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
        at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
        at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
        at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
        at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)
        at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)
        at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)
        at org.apache.spark.sql.Dataset.<init>(Dataset.scala:218)
        at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:98)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:95)
        at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:640)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:630)
        at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:671)
        at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:651)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:67)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:415)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:533)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1$adapted(SparkSQLCLIDriver.scala:527)
        at scala.collection.Iterator.foreach(Iterator.scala:943)
        at scala.collection.Iterator.foreach$(Iterator.scala:943)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
        at scala.collection.IterableLike.foreach(IterableLike.scala:74)
        at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
        at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processLine(SparkSQLCLIDriver.scala:527)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:307)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.base/java.lang.reflect.Method.invoke(Unknown Source)
        at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
        at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:1020)
        at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:192)
        at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:215)
        at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:91)
        at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1111)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1120)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
path must be absolute
java.lang.IllegalArgumentException: path must be absolute
        at com.google.common.base.Preconditions.checkArgument(Preconditions.java:92)
        at org.apache.hadoop.fs.s3a.s3guard.PathMetadata.<init>(PathMetadata.java:68)
        at org.apache.hadoop.fs.s3a.s3guard.PathMetadata.<init>(PathMetadata.java:60)
        at org.apache.hadoop.fs.s3a.s3guard.PathMetadata.<init>(PathMetadata.java:56)
        at org.apache.hadoop.fs.s3a.s3guard.S3Guard.putAndReturn(S3Guard.java:147)
        at org.apache.hadoop.fs.s3a.S3AFileSystem.innerGetFileStatus(S3AFileSystem.java:1876)
        at org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1812)
        at org.apache.iceberg.hadoop.HadoopCatalog.isDirectory(HadoopCatalog.java:176)
        at org.apache.iceberg.hadoop.HadoopCatalog.isNamespace(HadoopCatalog.java:377)
        at org.apache.iceberg.hadoop.HadoopCatalog.listNamespaces(HadoopCatalog.java:307)
        at org.apache.iceberg.catalog.SupportsNamespaces.listNamespaces(SupportsNamespaces.java:74)
        at org.apache.iceberg.spark.SparkCatalog.listNamespaces(SparkCatalog.java:434)
        at org.apache.spark.sql.execution.datasources.v2.ShowNamespacesExec.run(ShowNamespacesExec.scala:42)
        at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result$lzycompute(V2CommandExec.scala:43)
        at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result(V2CommandExec.scala:43)
        at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.executeCollect(V2CommandExec.scala:49)
        at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)
        at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)
        at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)
        at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
        at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
        at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)
        at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
        at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
        at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
        at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
        at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
        at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
        at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
        at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)
        at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)
        at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)
        at org.apache.spark.sql.Dataset.<init>(Dataset.scala:218)
        at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:98)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:95)
        at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:640)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:630)
        at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:671)
        at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:651)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:67)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:415)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:533)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1$adapted(SparkSQLCLIDriver.scala:527)
        at scala.collection.Iterator.foreach(Iterator.scala:943)
        at scala.collection.Iterator.foreach$(Iterator.scala:943)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
        at scala.collection.IterableLike.foreach(IterableLike.scala:74)
        at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
        at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processLine(SparkSQLCLIDriver.scala:527)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:307)
        at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.base/java.lang.reflect.Method.invoke(Unknown Source)
        at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
        at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:1020)
        at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:192)
        at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:215)
        at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:91)
        at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1111)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1120)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

2 replies

alberttwong Jun 7, 2024
Author

I couldn't figure it out but used a different spark-sql

spark-sql --packages com.amazonaws:aws-java-sdk-s3:1.11.271,org.apache.hadoop:hadoop-aws:2.10.2,org.apache.iceberg:iceberg-spark-runtime-3.4_2.12:1.5.2 \
--conf "spark.sql.extensions=org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions" \
--conf "spark.sql.catalog.spark_catalog=org.apache.iceberg.spark.SparkSessionCatalog" \
--conf "spark.sql.catalog.spark_catalog.type=hadoop" \
--conf "spark.sql.catalog.spark_catalog.warehouse=s3a://warehouse" \
--conf "spark.sql.catalog.hive_prod=org.apache.iceberg.spark.SparkCatalog" \
--conf "spark.sql.catalog.hive_prod.type=hadoop" \
--conf "spark.sql.catalog.hive_prod.warehouse=s3a://warehouse" \
--conf "spark.hadoop.fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"

alberttwong Jun 8, 2024
Author

this lets me go but I can't find a type=hadoop that works.

alberttwong · 2024-06-07T23:36:39Z

alberttwong
Jun 7, 2024
Author

CREATE SCHEMA iceberg_db LOCATION 's3a://warehouse/';
CREATE TABLE taxis 
(
  vendor_id bigint,
  trip_id bigint,
  trip_distance float,
  fare_amount double,
  store_and_fwd_flag string
)
USING iceberg
PARTITIONED BY (vendor_id) ;
INSERT INTO taxis VALUES (1, 1000371, 1.8, 15.32, 'N'), (2, 1000372, 2.5, 22.15, 'N'), (2, 1000373, 0.9, 9.01, 'N'), (1, 1000374, 8.4, 42.13, 'Y');

2 replies

alberttwong Jun 8, 2024
Author

24/06/08 03:56:22 ERROR SparkSQLDriver: Failed in [show schemas]
java.lang.IllegalArgumentException: path must be absolute

alberttwong Jun 8, 2024
Author

this seems like a dead end. I can't find a type=hadoop that works.

alberttwong · 2024-06-26T16:59:37Z

alberttwong
Jun 26, 2024
Author

summary of issue... xtable needs iceberg to generate metadata/version-hint.text to convert to hudi and delta.

0 replies

alberttwong · 2024-07-16T00:25:27Z

alberttwong
Jul 16, 2024
Author

cannot figure how to use hadoop 2.x libraries with spark 3.4. Works fine if you use hadoop 3.x libraries with spark 3.4

export AWS_SECRET_ACCESS_KEY=password
export AWS_ACCESS_KEY_ID=admin
export ENDPOINT=http://minio:9000
export AWS_REGION=us-east-1
spark-sql --packages org.apache.iceberg:iceberg-spark-runtime-3.4_2.12:1.5.2,org.apache.iceberg:iceberg-aws-bundle:1.5.2,org.apache.hadoop:hadoop-aws:3.3.4,software.amazon.awssdk:bundle:2.17.178,software.amazon.awssdk:url-connection-client:2.17.178 \
    --conf spark.hadoop.fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider \
    --conf spark.sql.defaultCatalog=iceberg \
    --conf spark.sql.catalog.iceberg=org.apache.iceberg.spark.SparkCatalog \
    --conf spark.sql.catalog.iceberg.warehouse=s3a://warehouse \
    --conf spark.sql.catalog.iceberg.type=hadoop

1 reply

alberttwong Jul 16, 2024
Author

don't use the create schema sql command.

CREATE TABLE taxis 
(
  vendor_id bigint,
  trip_id bigint,
  trip_distance float,
  fare_amount double,
  store_and_fwd_flag string
)
USING iceberg
PARTITIONED BY (vendor_id) ;
INSERT INTO taxis VALUES (1, 1000371, 1.8, 15.32, 'N'), (2, 1000372, 2.5, 22.15, 'N'), (2, 1000373, 0.9, 9.01, 'N'), (1, 1000374, 8.4, 42.13, 'Y');

alberttwong · 2024-07-16T17:09:17Z

alberttwong
Jul 16, 2024
Author

export AWS_SECRET_ACCESS_KEY=password
export AWS_ACCESS_KEY_ID=admin
export ENDPOINT=http://minio:9000
export AWS_REGION=us-east-1
cd /opt/xtable/jars/; java -jar xtable-utilities-0.1.0-SNAPSHOT-bundled.jar --datasetConfig xtable_iceberg.yaml -p core-site.xml

1 reply

alberttwong Jul 16, 2024
Author

root@spark:/opt/xtable/jars# cat xtable_iceberg.yaml 
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
sourceFormat: ICEBERG
targetFormats:
  - HUDI
  - DELTA
datasets:
  -
    tableBasePath: s3a://warehouse/taxis
    tableName: taxis
    partitionSpec: vendor_id:VALUE

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