aboutsummaryrefslogtreecommitdiff
path: root/bigtop-packages/src/charm/spark/layer-spark/config.yaml
blob: dee9f0077b9e2857ffb2a2f5511c6602973df2fa (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
options:
    driver_memory:
        type: string
        default: '1g'
        description: |
            Specify gigabytes (e.g. 1g) or megabytes (e.g. 1024m). If running
            in 'local' or 'standalone' mode, you may also specify a percentage
            of total system memory (e.g. 50%).
    executor_memory:
        type: string
        default: '1g'
        description: |
            Specify gigabytes (e.g. 1g) or megabytes (e.g. 1024m). If running
            in 'local' or 'standalone' mode, you may also specify a percentage
            of total system memory (e.g. 50%).
    spark_bench_enabled:
        type: boolean
        default: false
        description: |
            When set to 'true', this charm will download and install the
            Spark-Bench benchmark suite from the configured URLs. When set to
            'false' (the default), Spark-Bench will not be installed on the
            unit, though any data stored in hdfs:///user/ubuntu/spark-bench
            from previous installations will be preserved. Note that
            Spark-Bench has not been verified to work with Spark 2.1.x.
    spark_bench_url:
        type: string
        default: 'https://s3.amazonaws.com/jujubigdata/ibm/noarch/SparkBench-2.0-20170403.tgz#sha256=709caec6667dd82e42de25eb8bcd5763ca894e99e5c83c97bdfcf62cb1aa00c8'
        description: |
            URL (including hash) of a Spark-Bench tarball. By
            default, this points to a pre-built Spark-Bench binary based on
            sources in the upstream repository. This option is only valid when
            'spark_bench_enabled' is 'true'.
    spark_execution_mode:
        type: string
        default: 'standalone'
        description: |
            Options are "local", "standalone", "yarn-client", and
            "yarn-cluster". Consult the readme for details on these options.