Sqoop import postgres to S3 failing - amazon-s3

Question

I'm currently importing postgres data to hdfs. I'm planning to move the storage from hdfs to S3. When i'm trying to provide S3 location, the sqoop job is failing. I'm running it on EMR(emr-5.27.0) cluster and I've read/write access to that s3 bucket from all nodes in the cluster.
sqoop import \
--connect "jdbc:postgresql://<machine_ip>:<port>/<database>?sslfactory=org.postgresql.ssl.NonValidatingFactory&ssl=true" \
--username <username> \
--password-file <password_file_path> \
--table addresses \
--target-dir s3://my-bucket/data/temp \
--num-mappers 100 \
--split-by id \
--as-parquetfile
Exception is,
Warning: /usr/lib/sqoop/../accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
19/10/21 09:27:32 INFO sqoop.Sqoop: Running Sqoop version: 1.4.7
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/lib/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/lib/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
19/10/21 09:27:33 INFO manager.SqlManager: Using default fetchSize of 1000
19/10/21 09:27:33 INFO tool.CodeGenTool: Beginning code generation
19/10/21 09:27:33 INFO tool.CodeGenTool: Will generate java class as codegen_addresses
19/10/21 09:27:34 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM "addresses" AS t LIMIT 1
19/10/21 09:27:34 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/lib/hadoop-mapreduce
Note: /tmp/sqoop-hadoop/compile/412c4a70c10c6569443f4c38dbdc2c99/codegen_addresses.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
19/10/21 09:27:37 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/412c4a70c10c6569443f4c38dbdc2c99/codegen_addresses.jar
19/10/21 09:27:37 WARN manager.PostgresqlManager: It looks like you are importing from postgresql.
19/10/21 09:27:37 WARN manager.PostgresqlManager: This transfer can be faster! Use the --direct
19/10/21 09:27:37 WARN manager.PostgresqlManager: option to exercise a postgresql-specific fast path.
19/10/21 09:27:37 INFO mapreduce.ImportJobBase: Beginning import of addresses
19/10/21 09:27:37 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
19/10/21 09:27:39 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM "addresses" AS t LIMIT 1
19/10/21 09:27:39 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM "addresses" AS t LIMIT 1
19/10/21 09:27:39 INFO conf.HiveConf: Found configuration file file:/etc/hive/conf.dist/hive-site.xml
19/10/21 09:27:39 ERROR sqoop.Sqoop: Got exception running Sqoop: org.kitesdk.data.DatasetNotFoundException: Unknown dataset URI pattern: dataset:s3://<bucket>/<data>/temp
Check that JARs for s3 datasets are on the classpath
org.kitesdk.data.DatasetNotFoundException: Unknown dataset URI pattern: dataset:s3://<bucket>/<data>/temp
Check that JARs for s3 datasets are on the classpath
at org.kitesdk.data.spi.Registration.lookupDatasetUri(Registration.java:128)
at org.kitesdk.data.Datasets.exists(Datasets.java:624)
at org.kitesdk.data.Datasets.exists(Datasets.java:646)
at org.apache.sqoop.mapreduce.ParquetJob.configureImportJob(ParquetJob.java:118)
at org.apache.sqoop.mapreduce.DataDrivenImportJob.configureMapper(DataDrivenImportJob.java:132)
at org.apache.sqoop.mapreduce.ImportJobBase.runImport(ImportJobBase.java:264)
at org.apache.sqoop.manager.SqlManager.importTable(SqlManager.java:692)
at org.apache.sqoop.manager.PostgresqlManager.importTable(PostgresqlManager.java:127)
at org.apache.sqoop.tool.ImportTool.importTable(ImportTool.java:520)
at org.apache.sqoop.tool.ImportTool.run(ImportTool.java:628)
at org.apache.sqoop.Sqoop.run(Sqoop.java:147)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:76)
at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:183)
at org.apache.sqoop.Sqoop.runTool(Sqoop.java:234)
at org.apache.sqoop.Sqoop.runTool(Sqoop.java:243)
at org.apache.sqoop.Sqoop.main(Sqoop.java:252)
Note : The same sqoop command with hdfs target dir is working. I'm also able to manually write to s3 bucket from the cluster node (using aws s3 command).

Answer 1

The Kite SDK has been upgraded. All you have to do is to download the new SDK into EMR and run the sqoop command again.
Use wget to download the kite-data-s3-1.1.0.jar
wget https://repo1.maven.org/maven2/org/kitesdk/kite-data-s3/1.1.0/kite-data-s3-1.1.0.jar
Move the JAR to the Sqoop library directory (/usr/lib/sqoop/lib/)
sudo cp kite-data-s3-1.1.0.jar /usr/lib/sqoop/lib/
Grant permission on the JAR
sudo chmod 755 kite-data-s3-1.1.0.jar
Use the s3n connector to import the jar
sqoop import \
--connect "jdbc:postgresql://:/?sslfactory=org.postgresql.ssl.NonValidatingFactory&ssl=true" \
--username \
--password-file \
--table addresses \
--target-dir s3n://my-bucket/data/temp \
--num-mappers 100 \
--split-by id \
--as-parquetfile
Font: https://aws.amazon.com/premiumsupport/knowledge-center/unknown-dataset-uri-pattern-sqoop-emr/

Answer 2

There are two ways to sqoop to parquet -
Using --as-parquetfile
Using HCatalog
But both they way, its not possible to sqoop directly to parquet in EMR 5.X
Problem with both the approach -
Sqoop used Kite SDK to read/write Parquet and it has some limitations. And its not possible to use --as-parquetfile. EMR will remove Kite SDK in future as told by the AWS Support
Support Parquet through HCatalog has been added for hive (v2.4.0, v2.3.7) jira card and hive (v3.0.0) jira card. But EMR 5.X uses hive version 2.3.5.
What could be a workaround till now in EMR(v5.x):
Use a intermediate text table to pull the data. Use a separate hive query to copy the data from text to desired parquet table.

Answer 3

You'll need to change target-dir protocol from s3 to s3a:
sqoop import \
--connect "jdbc:postgresql://<machine_ip>:<port>/<database>?sslfactory=org.postgresql.ssl.NonValidatingFactory&ssl=true" \
--username <username> \
--password-file <password_file_path> \
--table addresses \
--target-dir s3a://my-bucket/data/temp \
--num-mappers 100 \
--split-by id \
--as-parquetfile

Answer 4

#Makubex, I was able to import after adding s3a as URI pattern,
But the time taken by the import job is too high.
I am using EMR 5.26.0. Do I need to do any configuration change for improving the time?

Answer 5

Please try executing sqoop command as specified below :
sqoop import \
--connect "jdbc:postgresql://<machine_ip>:<port>/<database>?sslfactory=org.postgresql.ssl.NonValidatingFactory&ssl=true" \
--username <username> \
--password-file <password_file_path> \
--num-mappers 100 \
--split-by id \
--table addresses \
--as-parquetfile \
--target-dir s3://my-bucket/data/temp
Do make sure the target directory doesn't exist in S3