Effective Sqoop: Best Practices, Pitfalls and Lessons

Effective SqoopAlex Silva

Principal Software [email protected]

mailto:[email protected]

Ten Best Practices1. It pays to use formatting arguments.

2. With the power of parallelism comes great responsibility!

3. Use direct connectors for fast prototyping and performance.

4. Use a boundary query for better performance.

5. Do not use the same table for import and export.

6. Use an options file for reusability.

7. Use the proper file format for your needs.

8. Prefer batch mode when exporting.

9. Use a staging table.

10.Aggregate data in Hive.

Copyright 2014 Rackspace

Formatting Arguments

Formatting Argument What is it for?

enclosed-by The field enclosing character.

escaped-by The escape character.

fields-terminated-by The field separator character.

lines-terminated-by The end of line char,

mysql-delimiters Default delimiters: fields (,) lines (\n) escaped-by (\) optionally-enclosed-by (')

optionally-enclosed-by The field enclosing character.

The default delimiters are: comma (,) for fields, newline (\n) for records, no quote character, and no escape character.


ID LABEL STATUS

1 Critical, test. ACTIVE

3 By “agent-nd01” DISABLED

$ sqoop import …

$ sqoop import --fields-terminated-by , --escaped-by \\ --enclosed-by '\"' ...

“1”,”Critical, test”, “ACTIVE”

“3”,“By \”agent-nd01\””,”DISABLED”1,”Critical, test”, ACTIVE

3,“By \”agent-nd01\””,DISABLED

1,Critical,test,ACTIVE

3,By “agent-nd01”,DISABLED

$ sqoop import --fields-terminated-by , --escaped-by \\ --optionally-enclosed-by '\"' ...

Sometimes the problemdoesn’t show up until much later…


Taming the Elephant

• Sqoop delegates all processing to Hadoop:

• Each mapper transfers a slice of the table.

• The parameter --num-mappers (defaults to 4) tells Sqoop how many mappers to use to slice the data.


How Many Mappers?

• The optimal number depends on a few variables:

• The database type.

• How does it handle parallelism internally?

• The server hardware and infrastructure.

• Overall impact to other requests.


Gotchas!• More mappers can lead to faster jobs, but

only up to a saturation point. This varies per table, job parameters, time of day and server availability.

• Too many mappers will increase the load on the database: people will notice!


Connectors• Two types of connectors: common (JDBC) and

direct (vendor specific batch tools).

Common Connectors

MySQL

PostgreSQL

Oracle

SQL Server

DB2

Generic

Direct Connectors

MySQL

PostgreSQL

Oracle

Teradata

And others


Direct Connectors• Performance!

• --direct parameter.

• Utilities need to be available on all task nodes.

• Escape characters, type mapping, column and row delimiters may not be supported.

• Binary formats don’t work.


Splitting Data• By default, the primary key is used.

• Prior to starting the transfer, Sqoop will retrieve the min/max values for this column.

• Changed column with the --split-by parameter:

• Required in tables with no index columns or multi-column keys.


Boundary Queries

What if your split-by column is skewed, table is not indexed or can be retrieved

from another table?

Use a boundary query to create the splits.

select min(<split-by>), max(<split-by>) from <table name>


Splitting Free form Queries

• By default, Sqoop will use the entire query as a subquery to calculate max/min: INEFFECTIVE!

• Solution: use a --boundary-query.

• Good choices:

• Store boundary values in a separate table.

• Good for incremental imports. (--last-value)

• Run query prior to Sqoop and save its output in a temporary table.


Options Files

• Reusable Arguments that do not change.

• Pass it to the command line via --options-file argument.

• Composition: more than one option file is allowed.







6. Use an options file for reusability

7. Use the proper file format for your needs

8. Prefer batch mode when exporting


10.Aggregate data in Hive


File Formats• Text (default):

• Non-binary data types.

• Simple and human-readable.

• Platform independent.

• Binary (AVRO and sequence files):

• Precise representation and with efficient storage.

• Good for Text containing separators.


Environment• A combination of text and AVRO files mostly.

• Why Avro?

• Compact, splittable binary encoding.

• Supports versioning and is language agnostic.

• Also used as a container for smaller files.


Exports• Experiment with batching multiple insert

statements together:

• --batch parameter

• sqoop.export.records.per.statement (100) property.

• sqoop.export.statements.per.transaction (100) property.


Batch Exports• The --batch parameter uses the JDBC batch

API. (addBatch/executeBatch)

• However…

• Implementation can vary among drivers.

• Some drivers actually perform worse in batch mode! (serialization and internal caches)


Batch Exports• The sqoop.export.records.per.statement

property will aggregate multiple rows inside one single insert statement.

• However…

• Not supported by all databases (most do.)

• Be aware that most dbs have limits on the maximum query size.


Batch Exports• The sqoop.export.records.per.transaction: how many insert statements will be issued per transaction.

• However…

• Exact behavior depends on database.

• Be aware of table-level write locks.


Which is better?• No silver bullet that applies to all use cases.

• Start with enabling batch import.

• Find out what’s the maximum query size for your database.

• Set the number of rows per statement to roughly that value.

• Go from there.


Staging Tables are our Friends

• All data is written to staging table first.

• Data is copied to the final destination iff all tasks succeed: all-or-nothing semantics.

• Structure must match exactly: columns and types.

• Staging table must exist before and must be empty. (--clear-staging-table parameter)


Hive• --hive-import parameter.

• BONUS: If table doesn’t exist, Sqoop will create it for you!

• Override default type mappings with --map-column-hive.

• Data is first loaded into HDFS and then loaded into Hive..

• Default behavior is append. (—hive-overwrite.)


Hive partitions• Two parameters:

• --hive-partition-key

• --hive-partition-value

• Current Limitations:

• One level of partitioning only.

• The partition value has to be an actual value and not a column name.


Hive and AVRO

• Currently not compatible!!

• Workaround is to create an EXTERNAL table.

CREATE EXTERNAL TABLE cs_atom_eventsROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.avro.AvroSerDe'STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat'OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat'LOCATION ‘/user/cloud-analytics/snapshot/atom_events/cloud-servers’TBLPROPERTIES (‘avro.schema.url’=‘hdfs:///user/cloud-analytics/avro/cs_cff_atom.avsc');


hdfs:///user/cloud-analytics/avro/cs_cff_atom.avsc'

Data Pipeline


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• Try it out!

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• Extract value from your data!

http://www.rackspace.com/cloud/big-data

Alex [email protected]

Thank you!


mailto:[email protected]

Effective Sqoop: Best Practices, Pitfalls and Lessons

Data & Analytics

Transcript of Effective Sqoop: Best Practices, Pitfalls and Lessons