Legacy Product

Fusion 5.10
    Fusion 5.10

    Use this job when you want to find outliers from a set of documents and attach labels for each outlier group.

    analyzerConfig - string

    LuceneTextAnalyzer schema for tokenization (JSON-encoded)

    >= 1 characters

    Default: { "analyzers": [{ "name": "StdTokLowerStop","charFilters": [ { "type": "htmlstrip" } ],"tokenizer": { "type": "standard" },"filters": [{ "type": "lowercase" },{ "type": "KStem" },{ "type": "length", "min": "2", "max": "32767" },{ "type": "fusionstop", "ignoreCase": "true", "format": "snowball", "words": "org/apache/lucene/analysis/snowball/english_stop.txt" }] }],"fields": [{ "regex": ".+", "analyzer": "StdTokLowerStop" } ]}

    dataFormat - stringrequired

    Spark-compatible format that contains training data (like 'solr', 'parquet', 'orc' etc)

    >= 1 characters

    Default: solr

    dataOutputFormat - string

    Spark-compatible output format (like 'solr', 'parquet', etc)

    >= 1 characters

    Default: solr

    distToCenterField - string

    Output field name for doc distance to its corresponding cluster center (measure how representative the doc is).

    Default: dist_to_center

    fieldToVectorize - stringrequired

    Solr field containing text training data. Data from multiple fields with different weights can be combined by specifying them as field1:weight1,field2:weight2 etc.

    >= 1 characters

    freqTermField - string

    Output field name for top frequent terms in each cluster. These may overlap with other clusters.

    Default: freq_terms

    id - stringrequired

    The ID for this Spark job. Used in the API to reference this job. Allowed characters: a-z, A-Z, dash (-) and underscore (_). Maximum length: 63 characters.

    <= 63 characters

    Match pattern: [a-zA-Z][_\-a-zA-Z0-9]*[a-zA-Z0-9]?

    maxDF - number

    Max number of documents the term can show up. value<1.0 denotes a percentage, value=1.0 denotes 100%, value>1.0 denotes the exact number.

    Default: 0.75

    minDF - number

    Min number of documents the term has to show up. value<1.0 denotes a percentage, value=1.0 denotes 100%, value>1.0 denotes the exact number.

    Default: 5

    modelId - string

    Identifier for the model to be trained; uses the supplied Spark Job ID if not provided.

    >= 1 characters

    norm - integer

    p-norm to normalize vectors with (choose -1 to turn normalization off)

    Default: 2

    Allowed values: -1012

    numKeywordsPerLabel - integer

    Number of Keywords needed for labeling each cluster.

    Default: 5

    outlierGroupIdField - string

    Output field name for unique outlier group id.

    Default: outlier_group_id

    outlierGroupLabelField - string

    Output field name for top frequent terms that are (mostly) unique for each outlier group as computed based on TF-IDF and group Id.

    Default: outlier_group_label

    outlierK - integer

    Number of clusters to help find outliers.

    Default: 10

    outlierThreshold - number

    Identify as outlier group if less than this percent of total documents. value<1.0 denotes a percentage, value=1.0 denotes 100%, value>1.0 denotes the exact number.

    Default: 0.01

    outputCollection - stringrequired

    Solr Collection to store model-labeled data to

    >= 1 characters

    outputOutliersOnly - boolean

    If true, only outliers are saved in the output collection, otherwise, the whole dataset is saved.

    Default: false

    partitionCols - string

    If writing to non-Solr sources, this field will accept a comma-delimited list of column names for partitioning the dataframe before writing to the external output

    randomSeed - integer

    For any deterministic pseudorandom number generation

    Default: 1234

    readOptions - array[object]

    Options used when reading input from Solr or other sources.

    object attributes:{key required : {
     display name: Parameter Name
     type: string
    }    value : {
     display name: Parameter Value
     type: string
    }    }

    sourceFields - string

    Solr fields to load (comma-delimited). Leave empty to allow the job to select the required fields to load at runtime.

    sparkConfig - array[object]

    Spark configuration settings.

    object attributes:{key required : {
     display name: Parameter Name
     type: string
    }    value : {
     display name: Parameter Value
     type: string
    }    }

    sparkSQL - string

    Use this field to create a Spark SQL query for filtering your input data. The input data will be registered as spark_input

    Default: SELECT * from spark_input

    trainingCollection - stringrequired

    Solr Collection containing documents to be clustered

    >= 1 characters

    trainingDataFilterQuery - string

    Solr query to use when loading training data if using Solr

    Default: *:*

    trainingDataFrameConfigOptions - object

    Additional spark dataframe loading configuration options

    trainingDataSamplingFraction - number

    Fraction of the training data to use

    <= 1

    exclusiveMaximum: false

    Default: 1

    type - stringrequired

    Default: outlier_detection

    Allowed values: outlier_detection

    uidField - stringrequired

    Field containing the unique ID for each document.

    >= 1 characters

    Default: id

    writeOptions - array[object]

    Options used when writing output to Solr or other sources

    object attributes:{key required : {
     display name: Parameter Name
     type: string
    }    value : {
     display name: Parameter Value
     type: string
    }    }