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Update hadoop docs to indicate new committers (#8060)

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Harshavardhana 5 years ago committed by GitHub
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      docs/bigdata/README.md

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docs/bigdata/README.md
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@ -4,7 +4,7 @@
![cloud-native](https://github.com/minio/minio/blob/master/docs/bigdata/images/image1.png?raw=true "cloud native architecture")
Kubernetes manages stateless Spark and Hive containers elastically on the compute nodes. Spark has native scheduler integration with Kubernetes. Hive, for legacy reasons, uses YARN scheduler on top of Kubernetes.
Kubernetes manages stateless Spark and Hive containers elastically on the compute nodes. Spark has native scheduler integration with Kubernetes. Hive, for legacy reasons, uses YARN scheduler on top of Kubernetes.
All access to MinIO object storage is via S3/SQL SELECT API. In addition to the compute nodes, MinIO containers are also managed by Kubernetes as stateful containers with local storage (JBOD/JBOF) mapped as persistent local volumes. This architecture enables multi-tenant MinIO, allowing isolation of data between customers.
@ -35,27 +35,63 @@ Navigate to **Custom core-site** to configure MinIO parameters for `_s3a_` conne
![s3a-config](https://github.com/minio/minio/blob/master/docs/bigdata/images/image5.png?raw=true "custom core-site")
Add the following optimal entries for _core-site.xml_ to configure _s3a_ with **MinIO**. Most important options here are
* _fs.s3a.access.key=minio_ (Access Key to access MinIO instance, this is obtained after the deployment on k8s)
* _fs.s3a.secret.key=minio123_ (Secret Key to access MinIO instance, this is obtained after the deployment on k8s)
* _fs.s3a.endpoint=`http://minio-address/`_
* _fs.s3a.multipart.size=128M_
* _fs.s3a.fast.upload=true_
* _fs.s3a.fast.upload.buffer=bytebuffer_
* _fs.s3a.path.style.access=true_
* _fs.s3a.block.size=256M_
* _fs.s3a.commiter.name=magic_
* _fs.s3a.committer.magic.enabled=true_
* _fs.s3a.committer.threads=16_
* _fs.s3a.connection.maximum=32_
* _fs.s3a.fast.upload.active.blocks=8_
* _fs.s3a.max.total.tasks=16_
* _fs.s3a.threads.core=32_
* _fs.s3a.threads.max=32_
* _mapreduce.outputcommitter.factory.scheme.s3a=org.apache.hadoop.fs.s3a.commit.S3ACommitterFactory_
![s3a-config](https://github.com/minio/minio/blob/master/docs/bigdata/images/image4.png?raw=true "custom core-site s3a")
```
sudo pip install yq
alias kv-pairify='xq ".configuration[]" | jq ".[]" | jq -r ".name + \"=\" + .value"'
```
Let's take for example a set of 12 compute nodes with an aggregate memory of *1.2TiB*, we need to do following settings for optimal results. Add the following optimal entries for _core-site.xml_ to configure _s3a_ with **MinIO**. Most important options here are
```
cat ${HADOOP_CONF_DIR}/core-site.xml | kv-pairify | grep "mapred"
mapred.maxthreads.generate.mapoutput=2 # Num threads to write map outputs
mapred.maxthreads.partition.closer=0 # Asynchronous map flushers
mapreduce.fileoutputcommitter.algorithm.version=2 # Use the latest committer version
mapreduce.job.reduce.slowstart.completedmaps=0.99 # 99% map, then reduce
mapreduce.reduce.shuffle.input.buffer.percent=0.9 # Min % buffer in RAM
mapreduce.reduce.shuffle.merge.percent=0.9 # Minimum % merges in RAM
mapreduce.reduce.speculative=false # Disable speculation for reducing
mapreduce.task.io.sort.factor=999 # Threshold before writing to disk
mapreduce.task.sort.spill.percent=0.9 # Minimum % before spilling to disk
```
S3A is the connector to use S3 and other S3-compatible object stores such as MinIO. MapReduce workloads typically interact with object stores in the same way they do with HDFS. These workloads rely on HDFS atomic rename functionality to complete writing data to the datastore. Object storage operations are atomic by nature and they do not require/implement rename API. The default S3A committer emulates renames through copy and delete APIs. This interaction pattern causes significant loss of performance because of the write amplification. *Netflix*, for example, developed two new staging committers - the Directory staging committer and the Partitioned staging committer - to take full advantage of native object storage operations. These committers do not require rename operation. The two staging committers were evaluated, along with another new addition called the Magic committer for benchmarking.
It was found that the directory staging committer was the fastest among the three, S3A connector should be configured with the following parameters for optimal results:
```
cat ${HADOOP_CONF_DIR}/core-site.xml | kv-pairify | grep "s3a"
fs.s3a.access.key=minio
fs.s3a.secret.key=minio123
fs.s3a.path.style.access=true
fs.s3a.block.size=512M
fs.s3a.buffer.dir=${hadoop.tmp.dir}/s3a
fs.s3a.committer.magic.enabled=false
fs.s3a.committer.name=directory
fs.s3a.committer.staging.abort.pending.uploads=true
fs.s3a.committer.staging.conflict-mode=append
fs.s3a.committer.staging.tmp.path=/tmp/staging
fs.s3a.committer.staging.unique-filenames=true
fs.s3a.connection.establish.timeout=5000
fs.s3a.connection.ssl.enabled=false
fs.s3a.connection.timeout=200000
fs.s3a.endpoint=http://minio:9000
fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem
fs.s3a.committer.threads=2048 # Number of threads writing to MinIO
fs.s3a.connection.maximum=8192 # Maximum number of concurrent conns
fs.s3a.fast.upload.active.blocks=2048 # Number of parallel uploads
fs.s3a.fast.upload.buffer=disk # Use disk as the buffer for uploads
fs.s3a.fast.upload=true # Turn on fast upload mode
fs.s3a.max.total.tasks=2048 # Maximum number of parallel tasks
fs.s3a.multipart.size=512M # Size of each multipart chunk
fs.s3a.multipart.threshold=512M # Size before using multipart uploads
fs.s3a.socket.recv.buffer=65536 # Read socket buffer hint
fs.s3a.socket.send.buffer=65536 # Write socket buffer hint
fs.s3a.threads.max=2048 # Maximum number of threads for S3A
```
The rest of the other optimization options are discussed in the links below
@ -78,13 +114,35 @@ Navigate to “**Custom spark-defaults**” to configure MinIO parameters for `_
Add the following optimal entries for _spark-defaults.conf_ to configure Spark with **MinIO**.
* _spark.hadoop.fs.s3a.committer.magic.enabled=true_
* _spark.hadoop.fs.s3a.committer.name=magic_
* _spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem_
* _spark.hadoop.fs.s3a.path.style.access=true_
* _spark.hadoop.mapreduce.outputcommitter.factory.scheme.s3a=org.apache.hadoop.fs.s3a.commit.S3ACommitterFactory_
![spark-config](https://github.com/minio/minio/blob/master/docs/bigdata/images/image8.png?raw=true "spark custom configuration")
```
spark.hadoop.fs.s3a.access.key minio
spark.hadoop.fs.s3a.secret.key minio123
spark.hadoop.fs.s3a.path.style.access true
spark.hadoop.fs.s3a.block.size 512M
spark.hadoop.fs.s3a.buffer.dir ${hadoop.tmp.dir}/s3a
spark.hadoop.fs.s3a.committer.magic.enabled false
spark.hadoop.fs.s3a.committer.name directory
spark.hadoop.fs.s3a.committer.staging.abort.pending.uploads true
spark.hadoop.fs.s3a.committer.staging.conflict-mode append
spark.hadoop.fs.s3a.committer.staging.tmp.path /tmp/staging
spark.hadoop.fs.s3a.committer.staging.unique-filenames true
spark.hadoop.fs.s3a.committer.threads 2048 # number of threads writing to MinIO
spark.hadoop.fs.s3a.connection.establish.timeout 5000
spark.hadoop.fs.s3a.connection.maximum 8192 # maximum number of concurrent conns
spark.hadoop.fs.s3a.connection.ssl.enabled false
spark.hadoop.fs.s3a.connection.timeout 200000
spark.hadoop.fs.s3a.endpoint http://minio:9000
spark.hadoop.fs.s3a.fast.upload.active.blocks 2048 # number of parallel uploads
spark.hadoop.fs.s3a.fast.upload.buffer disk # use disk as the buffer for uploads
spark.hadoop.fs.s3a.fast.upload true # turn on fast upload mode
spark.hadoop.fs.s3a.impl org.apache.hadoop.spark.hadoop.fs.s3a.S3AFileSystem
spark.hadoop.fs.s3a.max.total.tasks 2048 # maximum number of parallel tasks
spark.hadoop.fs.s3a.multipart.size 512M # size of each multipart chunk
spark.hadoop.fs.s3a.multipart.threshold 512M # size before using multipart uploads
spark.hadoop.fs.s3a.socket.recv.buffer 65536 # read socket buffer hint
spark.hadoop.fs.s3a.socket.send.buffer 65536 # write socket buffer hint
spark.hadoop.fs.s3a.threads.max 2048 # maximum number of threads for S3A
```
Once the config changes are applied, proceed to restart **Spark** services.
@ -102,12 +160,14 @@ Navigate to “**Custom hive-site**” to configure MinIO parameters for `_s3a_`
Add the following optimal entries for `hive-site.xml` to configure Hive with **MinIO**.
* _hive.blobstore.use.blobstore.as.scratchdir=true_
* _hive.exec.input.listing.max.threads=50_
* _hive.load.dynamic.partitions.thread=25_
* _hive.metastore.fshandler.threads=50_
* _hive.mv.files.threads=40_
* _mapreduce.input.fileinputformat.list-status.num-threads=50_
```
hive.blobstore.use.blobstore.as.scratchdir=true
hive.exec.input.listing.max.threads=50
hive.load.dynamic.partitions.thread=25
hive.metastore.fshandler.threads=50
hive.mv.files.threads=40
mapreduce.input.fileinputformat.list-status.num-threads=50
```
For more information about these options please visit [https://www.cloudera.com/documentation/enterprise/5-11-x/topics/admin_hive_on_s3_tuning.html](https://www.cloudera.com/documentation/enterprise/5-11-x/topics/admin_hive_on_s3_tuning.html)

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