title | titleSuffix | description | author | ms.author | ms.reviewer | ms.date | ms.service | ms.subservice | ms.topic |
---|---|---|---|---|---|---|---|---|---|
Apache Spark and Apache Hadoop |
Configure Apache Spark and Apache Hadoop in Big Data Clusters |
SQL Server Big Data Clusters allow Spark and HDFS solutions. Learn how to configure them. |
WilliamDAssafMSFT |
wiassaf |
mikeray |
08/04/2020 |
sql |
big-data-cluster |
conceptual |
[!INCLUDEbig-data-clusters-banner-retirement]
In order to configure Apache Spark and Apache Hadoop in Big Data Clusters, you need to modify the cluster profile at deployment time.
A Big Data Cluster has four configuration categories:
sql
hdfs
spark
gateway
sql
, hdfs
, spark
, sql
are services. Each service maps to the same named configuration category. All gateway configurations go to category gateway
.
For example, all configurations in service hdfs
belong to category hdfs
. Note that all Hadoop (core-site), HDFS and Zookeeper configurations belong to category hdfs
; all Livy, Spark, Yarn, Hive, Metastore configurations belong to category spark
.
Supported configurations lists Apache Spark & Hadoop properties that you can configure when you deploy a SQL Server Big Data Cluster.
The following sections list properties that you can't modify in a cluster:
In the cluster profile there are resources and services. At deployment time, we can specify configurations in one of two ways:
-
First, at the resource level:
The following examples are the patch files for the profile:
{ "op": "add", "path": "spec.resources.zookeeper.spec.settings", "value": { "hdfs": { "zoo-cfg.syncLimit": "6" } } }
Or:
{ "op": "add", "path": "spec.resources.gateway.spec.settings", "value": { "gateway": { "gateway-site.gateway.httpclient.socketTimeout": "95s" } } }
-
Second, at the service level. Assign multiple resources to a service, and specify configurations to the service.
The following is an example of the patch file for the profile for setting HDFS block size:
{
"op": "add",
"path": "spec.services.hdfs.settings",
"value": {
"hdfs-site.dfs.block.size": "268435456"
}
}
The service hdfs
is defined as:
{
"spec": {
"services": {
"hdfs": {
"resources": [
"nmnode-0",
"zookeeper",
"storage-0",
"sparkhead"
],
"settings":{
"hdfs-site.dfs.block.size": "268435456"
}
}
}
}
}
Note
Resource level configurations override service level configurations. One resource can be assigned to multiple services.
In addition to the supported Apache configurations, we also offer the ability to configure whether or not Spark jobs can run in the Storage pool. This boolean value, includeSpark
, is in the bdc.json
configuration file at spec.resources.storage-0.spec.settings.spark
.
An example storage pool definition in bdc.json may look like this:
...
"storage-0": {
"metadata": {
"kind": "Pool",
"name": "default"
},
"spec": {
"type": "Storage",
"replicas": 2,
"settings": {
"spark": {
"includeSpark": "true"
}
}
}
}
Configurations can only be specified at category level. To specify multiple configurations with the same sub-category, we cannot extract the common prefix in cluster profile.
{
"op": "add",
"path": "spec.services.hdfs.settings.core-site.hadoop",
"value": {
"proxyuser.xyz.users": "*",
"proxyuser.abc.users": "*"
}
}
- Apache Spark & Apache Hadoop (HDFS) configuration properties.
- [[!INCLUDE azure-data-cli-azdata] reference](../azdata/reference/reference-azdata.md)
- [Introducing [!INCLUDEbig-data-clusters-2019]](big-data-cluster-overview.md)