distcp gobblin

Distcp-ng:Replicating massive datasets with Gobblin

Issac BuenrostroGobblin Meetup, Jun 2016

Outline

1 Motivation

2 Architecture

3 Features

4 Hive Copy

5 Future

Motivation

 Distributed Copy Copy files between Hadoop compatible file systems.

What is Distcp?

Motivation

1.Continuous replication of datasets.

2.Efficient file listing.

• Reduce file system rpc calls• Alternate listing services first-class citizens.

3.Dataset awareness: prioritization, notification, etc.

4.Failure isolation.

5.Operational metrics, notifications, data availability triggers.

6.Portability.

Architecture

Distcp Gobblin Architecture

Copyable Dataset- Basic

Copy Entities - Advanced

Pre / Post publish stepsCopy Entities – Run before or after publish (NOOP in Task)

Features

Recursive Copy

Most similar to distcp

Copy all files under an input path

Accepts path filter

Features

Source Converter TargetHadoop File System

SFTP

Apache server filer

Hive

…

Byte-level stream transformations:

• Encrypt / Decrypt

• (Un) Gzip

• Untar

Atomic publishing

Data availability notification

Hive Registration

File deletion / sync

File Sets

Distcp atomic unit, single dataset can be split into multiple file sets

1. All-or-nothing publish*

2. Isolation: failed file set does not affect other file sets

3. Event emitted on publish per file and file set

* best-effort. Future: use write-ahead log for better guarantee.

Smart file limits

Limit the number of files copied in a single run

1. File sets are never split

2. Soft limit: stop processing new file sets, currently running file sets can finish

3. Hard limit: do not accept any more files

4. Prioritize file sets (Future)

Unpublished File Persistence

1. Files that were copied successfully but not published are persisted in private directory. (File set failure, permission failure, etc.)

2. Future run identifies persisted file, reuse instead of re-copying.

3. Time-based automatic retention on persist directory.

Hive Copy

Hive Copy

Copy Hive tables between Hive metastores

1. Determine files under each table / partition

2. Diff files in source / target

3. Copy necessary files

4. Register tables / partitions on target

5. Deregister partitions missing in source

6. (Optional) Delete files for deregistered partitions

Hive Copy Configuration

job.name=distcpNgExample

# Source and target metastoreshive.dataset.hive.metastore.uri=thrift://mysource.hive:9000hive.dataset.copy.target.metastore.uri=thrift://mytarget:9000

gobblin.copy.preserved.attributes=rgbp # Preserve attributes

# Database and tables copyhive.dataset.whitelist=events.loginEvent|logoutEvent,metrics

hive.dataset.copy.locations.listing.skipHiddenPaths=true # Skip hidden paths

# Use registration time to determine whether a partition should be skippedhive.dataset.copy.fast.partition.skip.predicate=gobblin.data.management.copy.predicates.RegistrationTimeSkipPredicate

# Partition filterhive.dataset.copy.partition.filter.generator=gobblin.data.management.copy.hive.filter.LookbackPartitionFilterGeneratorhive.dataset.partition.filter.datetime.column=datepartitionhive.dataset.partition.filter.datetime.lookback=P7Dhive.dataset.partition.filter.datetime.format=YYYY-MM-dd-HH

Hive Copy

Candidate FilesExisting files at expected target location.

• Different location• Schema incompatible• …

Hive Copy - Numbers

100+ tables3000+ partitions20,000+ new files per hour2TB+ new data per hour

File listing 30k files: < 30sCopy 30k files, 5TB: ~20 min

Current bottlenecks

Work unit serialization• ~100 work units / second

Bad nodes in Hadoop cluster• Need speculation

Serial publishing of file sets• Solution in progress

Gobblin Distcp vs ReAir

Reair: Hive warehouse data replication (Airbnb)Offers batch and incremental replication

Gobblin Distcp ReAirFile listing and modification times for incremental changes

MySQL and audit log hook store for incremental changes

Portable Gobblin job (MR, thread based, Helix)

MR job

Same framework can copy non-Hive data

Monitoring / Web UI (in progress for Gobblin)

Future

Distcp continuous service

Next Steps

1 Simple CLI launcher

2 Dataset / file set prioritization

3 Global network throttling

4 Large file splitting

5 Least-congested path optimization

Find out more:

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