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Version: 2.3.10

FakeSource

FakeSource connector

Support Those Engines​

Spark
Flink
SeaTunnel Zeta

Description​

The FakeSource is a virtual data source, which randomly generates the number of rows according to the data structure of the user-defined schema, just for some test cases such as type conversion or connector new feature testing

Key Features​

Source Options​

NameTypeRequiredDefaultDescription
tables_configslistno-Define Multiple FakeSource, each item can contains the whole fake source config description below
schemaconfigyes-Define Schema information
rowsconfigno-The row list of fake data output per degree of parallelism see title Options rows Case.
row.numintno5The total number of data generated per degree of parallelism
split.numintno1the number of splits generated by the enumerator for each degree of parallelism
split.read-intervallongno1The interval(mills) between two split reads in a reader
map.sizeintno5The size of map type that connector generated
array.sizeintno5The size of array type that connector generated
bytes.lengthintno5The length of bytes type that connector generated
string.lengthintno5The length of string type that connector generated
string.fake.modestringnorangeThe fake mode of generating string data, support range and template, default range，if use configured it to template, user should also configured string.template option
string.templatelistno-The template list of string type that connector generated, if user configured it, connector will randomly select an item from the template list
tinyint.fake.modestringnorangeThe fake mode of generating tinyint data, support range and template, default range，if use configured it to template, user should also configured tinyint.template option
tinyint.mintinyintno0The min value of tinyint data that connector generated
tinyint.maxtinyintno127The max value of tinyint data that connector generated
tinyint.templatelistno-The template list of tinyint type that connector generated, if user configured it, connector will randomly select an item from the template list
smallint.fake.modestringnorangeThe fake mode of generating smallint data, support range and template, default range，if use configured it to template, user should also configured smallint.template option
smallint.minsmallintno0The min value of smallint data that connector generated
smallint.maxsmallintno32767The max value of smallint data that connector generated
smallint.templatelistno-The template list of smallint type that connector generated, if user configured it, connector will randomly select an item from the template list
int.fake.templatestringnorangeThe fake mode of generating int data, support range and template, default range，if use configured it to template, user should also configured int.template option
int.minintno0The min value of int data that connector generated
int.maxintno0x7fffffffThe max value of int data that connector generated
int.templatelistno-The template list of int type that connector generated, if user configured it, connector will randomly select an item from the template list
bigint.fake.modestringnorangeThe fake mode of generating bigint data, support range and template, default range，if use configured it to template, user should also configured bigint.template option
bigint.minbigintno0The min value of bigint data that connector generated
bigint.maxbigintno0x7fffffffffffffffThe max value of bigint data that connector generated
bigint.templatelistno-The template list of bigint type that connector generated, if user configured it, connector will randomly select an item from the template list
float.fake.modestringnorangeThe fake mode of generating float data, support range and template, default range，if use configured it to template, user should also configured float.template option
float.minfloatno0The min value of float data that connector generated
float.maxfloatno0x1.fffffeP+127The max value of float data that connector generated
float.templatelistno-The template list of float type that connector generated, if user configured it, connector will randomly select an item from the template list
double.fake.modestringnorangeThe fake mode of generating float data, support range and template, default range，if use configured it to template, user should also configured double.template option
double.mindoubleno0The min value of double data that connector generated
double.maxdoubleno0x1.fffffffffffffP+1023The max value of double data that connector generated
double.templatelistno-The template list of double type that connector generated, if user configured it, connector will randomly select an item from the template list
vector.dimensionintno4Dimension of the generated vector, excluding binary vectors
binary.vector.dimensionintno8Dimension of the generated binary vector
vector.float.minfloatno0The min value of float data in vector that connector generated
vector.float.maxfloatno0x1.fffffeP+127The max value of float data in vector that connector generated
common-optionsno-Source plugin common parameters, please refer to Source Common Options for details

Task Example​

Simple:​

This example Randomly generates data of a specified type. If you want to learn how to declare field types, click here.

schema = {
  fields {
    c_map = "map<string, array<int>>"
    c_map_nest = "map<string, {c_int = int, c_string = string}>"
    c_array = "array<int>"
    c_string = string
    c_boolean = boolean
    c_tinyint = tinyint
    c_smallint = smallint
    c_int = int
    c_bigint = bigint
    c_float = float
    c_double = double
    c_decimal = "decimal(30, 8)"
    c_null = "null"
    c_bytes = bytes
    c_date = date
    c_timestamp = timestamp
    c_row = {
      c_map = "map<string, map<string, string>>"
      c_array = "array<int>"
      c_string = string
      c_boolean = boolean
      c_tinyint = tinyint
      c_smallint = smallint
      c_int = int
      c_bigint = bigint
      c_float = float
      c_double = double
      c_decimal = "decimal(30, 8)"
      c_null = "null"
      c_bytes = bytes
      c_date = date
      c_timestamp = timestamp
    }
  }
}

Random Generation​

16 data matching the type are randomly generated

source {
  # This is a example input plugin **only for test and demonstrate the feature input plugin**
  FakeSource {
    row.num = 16
    schema = {
      fields {
        c_map = "map<string, string>"
        c_array = "array<int>"
        c_string = string
        c_boolean = boolean
        c_tinyint = tinyint
        c_smallint = smallint
        c_int = int
        c_bigint = bigint
        c_float = float
        c_double = double
        c_decimal = "decimal(30, 8)"
        c_null = "null"
        c_bytes = bytes
        c_date = date
        c_timestamp = timestamp
      }
    }
    plugin_output = "fake"
  }
}

Customize the data content Simple:​

This is a self-defining data source information, defining whether each piece of data is an add or delete modification operation, and defining what each field stores

source {
  FakeSource {
    schema = {
      fields {
        c_map = "map<string, string>"
        c_array = "array<int>"
        c_string = string
        c_boolean = boolean
        c_tinyint = tinyint
        c_smallint = smallint
        c_int = int
        c_bigint = bigint
        c_float = float
        c_double = double
        c_decimal = "decimal(30, 8)"
        c_null = "null"
        c_bytes = bytes
        c_date = date
        c_timestamp = timestamp
      }
    }
    rows = [
      {
        kind = INSERT
        fields = [{"a": "b"}, [101], "c_string", true, 117, 15987, 56387395, 7084913402530365000, 1.23, 1.23, "2924137191386439303744.39292216", null, "bWlJWmo=", "2023-04-22", "2023-04-22T23:20:58"]
      }
      {
        kind = UPDATE_BEFORE
        fields = [{"a": "c"}, [102], "c_string", true, 117, 15987, 56387395, 7084913402530365000, 1.23, 1.23, "2924137191386439303744.39292216", null, "bWlJWmo=", "2023-04-22", "2023-04-22T23:20:58"]
      }
      {
        kind = UPDATE_AFTER
        fields = [{"a": "e"}, [103], "c_string", true, 117, 15987, 56387395, 7084913402530365000, 1.23, 1.23, "2924137191386439303744.39292216", null, "bWlJWmo=", "2023-04-22", "2023-04-22T23:20:58"]
      }
      {
        kind = DELETE
        fields = [{"a": "f"}, [104], "c_string", true, 117, 15987, 56387395, 7084913402530365000, 1.23, 1.23, "2924137191386439303744.39292216", null, "bWlJWmo=", "2023-04-22", "2023-04-22T23:20:58"]
      }
    ]
  }
}

Due to the constraints of the HOCON specification, users cannot directly create byte sequence objects. FakeSource uses strings to assign bytes type values. In the example above, the bytes type field is assigned "bWlJWmo=", which is encoded from "miIZj" with base64. Hence, when assigning values to bytes type fields, please use strings encoded with base64.

Specified Data number Simple:​

This case specifies the number of data generated and the length of the generated value

FakeSource {
  row.num = 10
  map.size = 10
  array.size = 10
  bytes.length = 10
  string.length = 10
  schema = {
    fields {
      c_map = "map<string, array<int>>"
      c_array = "array<int>"
      c_string = string
      c_boolean = boolean
      c_tinyint = tinyint
      c_smallint = smallint
      c_int = int
      c_bigint = bigint
      c_float = float
      c_double = double
      c_decimal = "decimal(30, 8)"
      c_null = "null"
      c_bytes = bytes
      c_date = date
      c_timestamp = timestamp
      c_row = {
        c_map = "map<string, map<string, string>>"
        c_array = "array<int>"
        c_string = string
        c_boolean = boolean
        c_tinyint = tinyint
        c_smallint = smallint
        c_int = int
        c_bigint = bigint
        c_float = float
        c_double = double
        c_decimal = "decimal(30, 8)"
        c_null = "null"
        c_bytes = bytes
        c_date = date
        c_timestamp = timestamp
      }
    }
  }
}

Template data Simple:​

Randomly generated according to the specified template

Using template

FakeSource {
  row.num = 5
  string.fake.mode = "template"
  string.template = ["tyrantlucifer", "hailin", "kris", "fanjia", "zongwen", "gaojun"]
  tinyint.fake.mode = "template"
  tinyint.template = [1, 2, 3, 4, 5, 6, 7, 8, 9]
  smalling.fake.mode = "template"
  smallint.template = [10, 11, 12, 13, 14, 15, 16, 17, 18, 19]
  int.fake.mode = "template"
  int.template = [20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
  bigint.fake.mode = "template"
  bigint.template = [30, 31, 32, 33, 34, 35, 36, 37, 38, 39]
  float.fake.mode = "template"
  float.template = [40.0, 41.0, 42.0, 43.0]
  double.fake.mode = "template"
  double.template = [44.0, 45.0, 46.0, 47.0]
  schema {
    fields {
      c_string = string
      c_tinyint = tinyint
      c_smallint = smallint
      c_int = int
      c_bigint = bigint
      c_float = float
      c_double = double
    }
  }
}

Range data Simple:​

The specified data generation range is randomly generated

FakeSource {
  row.num = 5
  string.template = ["tyrantlucifer", "hailin", "kris", "fanjia", "zongwen", "gaojun"]
  tinyint.min = 1
  tinyint.max = 9
  smallint.min = 10
  smallint.max = 19
  int.min = 20
  int.max = 29
  bigint.min = 30
  bigint.max = 39
  float.min = 40.0
  float.max = 43.0
  double.min = 44.0
  double.max = 47.0
  schema {
    fields {
      c_string = string
      c_tinyint = tinyint
      c_smallint = smallint
      c_int = int
      c_bigint = bigint
      c_float = float
      c_double = double
    }
  }
}

Generate Multiple tables​

This is a case of generating a multi-data source test.table1 and test.table2

FakeSource {
  tables_configs = [
    {
      row.num = 16
      schema {
        table = "test.table1"
        fields {
          c_string = string
          c_tinyint = tinyint
          c_smallint = smallint
          c_int = int
          c_bigint = bigint
          c_float = float
          c_double = double
        }
      }
    },
    {
      row.num = 17
      schema {
        table = "test.table2"
        fields {
          c_string = string
          c_tinyint = tinyint
          c_smallint = smallint
          c_int = int
          c_bigint = bigint
          c_float = float
          c_double = double
        }
      }
    }
  ]
}

Options rows Case​

rows = [
  {
    kind = INSERT
    fields = [1, "A", 100]
  },
  {
    kind = UPDATE_BEFORE
    fields = [1, "A", 100]
  },
  {
    kind = UPDATE_AFTER
    fields = [1, "A_1", 100]
  },
  {
    kind = DELETE
    fields = [1, "A_1", 100]
  }
]

Options table-names Case​


source {
  # This is a example source plugin **only for test and demonstrate the feature source plugin**
  FakeSource {
    table-names = ["test.table1", "test.table2", "test.table3"]
    parallelism = 1
    schema = {
      fields {
        name = "string"
        age = "int"
      }
    }
  }
}

Options defaultValue Case​

Custom data can be generated by row and columns. For the time type, obtain the current time by CURRENT_TIMESTAMP 、CURRENT_TIME 、 CURRENT_DATE

    schema = {
        fields {
            pk_id = bigint
            name = string
            score = int
            time1 = timestamp
            time2 = time
            time3 = date
        }
    }
    # use rows
    rows = [
        {
            kind = INSERT
            fields = [1, "A", 100, CURRENT_TIMESTAMP, CURRENT_TIME, CURRENT_DATE]
        }
    ]
      schema = {
          # use columns
           columns = [
           {
              name = book_publication_time
              type = timestamp
              defaultValue = "2024-09-12 15:45:30"
              comment = "book publication time"
           },
           {
              name = book_publication_time2
              type = timestamp
              defaultValue = CURRENT_TIMESTAMP
              comment = "book publication time2"
           },
           {
              name = book_publication_time3
              type = time
              defaultValue = "15:45:30"
              comment = "book publication time3"
           },
           {
              name = book_publication_time4
              type = time
              defaultValue = CURRENT_TIME
              comment = "book publication time4"
           },
           {
              name = book_publication_time5
              type = date
              defaultValue = "2024-09-12"
              comment = "book publication time5"
           },
           {
              name = book_publication_time6
              type = date
              defaultValue = CURRENT_DATE
              comment = "book publication time6"
           }
       ]
      }

Use Vector Example​


source {
  FakeSource {
      row.num = 10
      # Low priority 
      vector.dimension= 4
      binary.vector.dimension = 8
      # Low priority 
      schema = {
           table = "simple_example"
           columns = [
           {
              name = book_id
              type = bigint
              nullable = false
              defaultValue = 0
              comment = "primary key id"
           },
            {
              name = book_intro_1
              type = binary_vector
              columnScale =8
              comment = "vector"
           },
           {
              name = book_intro_2
              type = float16_vector
              columnScale =4
              comment = "vector"
           },
           {
              name = book_intro_3
              type = bfloat16_vector
              columnScale =4
              comment = "vector"
           },
           {
              name = book_intro_4
              type = sparse_float_vector
              columnScale =4
              comment = "vector"
           }
       ]
     }
  }
}


Changelog​

Change Log
ChangeCommitVersion
[improve] fake source options (#8950)https://github.com/apache/seatunnel/commit/f8c47fb5f2.3.10
[Improve] restruct connector common options (#8634)https://github.com/apache/seatunnel/commit/f3499a6ee2.3.10
[Feature][API] Support timestamp with timezone offset (#8367)https://github.com/apache/seatunnel/commit/e18bfeabd2.3.9
[Improve][dist]add shade check rule (#8136)https://github.com/apache/seatunnel/commit/51ef800012.3.9
[Improve][API] Unified tables_configs and table_list (#8100)https://github.com/apache/seatunnel/commit/84c0b8d662.3.9
[Feature][Core] Rename result_table_name/source_table_name to plugin_input/plugin_output (#8072)https://github.com/apache/seatunnel/commit/c7bbd322d2.3.9
[Improve][Fake] Improve memory usage when split size is large (#7821)https://github.com/apache/seatunnel/commit/2d41b024c2.3.9
[Improve][Connector-V2] Time supports default value (#7639)https://github.com/apache/seatunnel/commit/33978689f2.3.8
[Improve][Connector-V2] Fake supports column configuration (#7503)https://github.com/apache/seatunnel/commit/39162a4e02.3.8
[Feature][Core] Add event notify for all connector (#7501)https://github.com/apache/seatunnel/commit/d71337b0e2.3.8
[Improve][Connector-V2] update vectorType (#7446)https://github.com/apache/seatunnel/commit/1bba723852.3.8
[Feature][Connector-V2] Fake Source support produce vector data (#7401)https://github.com/apache/seatunnel/commit/6937d10ac2.3.8
[Feature][Kafka] Support multi-table source read (#5992)https://github.com/apache/seatunnel/commit/60104602d2.3.6
[Feature][Doris] Add Doris type converter (#6354)https://github.com/apache/seatunnel/commit/5189991842.3.6
[Feature][Core] Support event listener for job (#6419)https://github.com/apache/seatunnel/commit/831d0022e2.3.5
[Fix][FakeSource] fix random from template not include the latest value issue (#6438)https://github.com/apache/seatunnel/commit/6ec16ac462.3.5
[Improve][Catalog] Use default tablepath when can not get the tablepath from source config (#6276)https://github.com/apache/seatunnel/commit/f8158bb802.3.4
[Improve][Connector-V2] Replace CommonErrorCodeDeprecated.JSON_OPERATION_FAILED (#5978)https://github.com/apache/seatunnel/commit/456cd17712.3.4
FakeSource support generate different CatalogTable for MultipleTable (#5766)https://github.com/apache/seatunnel/commit/a8b93805e2.3.4
[Improve][Common] Introduce new error define rule (#5793)https://github.com/apache/seatunnel/commit/9d1b2582b2.3.4
[Improve] Add default implement for SeaTunnelSource::getProducedType (#5670)https://github.com/apache/seatunnel/commit/a04add6992.3.4
Support config tableIdentifier for schema (#5628)https://github.com/apache/seatunnel/commit/652921fb72.3.4
[Feature] Add table-names from FakeSource/Assert to produce/assert multi-table (#5604)https://github.com/apache/seatunnel/commit/2c67cd8f32.3.4
Support config column/primaryKey/constraintKey in schema (#5564)https://github.com/apache/seatunnel/commit/eac76b4e52.3.4
[Improve][CheckStyle] Remove useless 'SuppressWarnings' annotation of checkstyle. (#5260)https://github.com/apache/seatunnel/commit/51c0d709b2.3.4
[improve][zeta] fix zeta bugshttps://github.com/apache/seatunnel/commit/3a82e8b392.3.1
[chore] Code format with spotless plugin.https://github.com/apache/seatunnel/commit/291214ad62.3.1
Merge branch 'dev' into merge/cdchttps://github.com/apache/seatunnel/commit/4324ee1912.3.1
[Improve][Project] Code format with spotless plugin.https://github.com/apache/seatunnel/commit/423b583032.3.1
[improve][api] Refactoring schema parse (#4157)https://github.com/apache/seatunnel/commit/b2f573a132.3.1
[Improve][build] Give the maven module a human readable name (#4114)https://github.com/apache/seatunnel/commit/d7cd601052.3.1
[Improve][Project] Code format with spotless plugin. (#4101)https://github.com/apache/seatunnel/commit/a2ab166562.3.1
[Improve][Connector-fake] Optimizing Data Generation Strategies refer to #4004 (#4061)https://github.com/apache/seatunnel/commit/c7c596a6d2.3.1
[Improve][Connector-V2][Fake] Improve fake connector (#3932)https://github.com/apache/seatunnel/commit/31f12431d2.3.1
[Feature][Connector-v2][StarRocks] Support write cdc changelog event(INSERT/UPDATE/DELETE) (#3865)https://github.com/apache/seatunnel/commit/8e3d158c02.3.1
[Feature][Connector] add get source method to all source connector (#3846)https://github.com/apache/seatunnel/commit/417178fb82.3.1
[Feature][API &amp; Connector &amp; Doc] add parallelism and column projection interface (#3829)https://github.com/apache/seatunnel/commit/b9164b8ba2.3.1
[Hotfix][OptionRule] Fix option rule about all connectors (#3592)https://github.com/apache/seatunnel/commit/226dc6a112.3.0
[Improve][Connector-V2][Fake] Unified exception for fake source connector (#3520)https://github.com/apache/seatunnel/commit/f371ad5822.3.0
[Connector-V2][Fake] Add Fake TableSourceFactory (#3345)https://github.com/apache/seatunnel/commit/74b61c33a2.3.0
[Connector-V2][ElasticSearch] Add ElasticSearch Source/Sink Factory (#3325)https://github.com/apache/seatunnel/commit/38254e3f22.3.0
[Improve][Engine] Improve Engine performance. (#3216)https://github.com/apache/seatunnel/commit/7393c47322.3.0
[hotfix][connector][fake] fix FakeSourceSplitEnumerator assigning duplicate splits when restoring (#3112)https://github.com/apache/seatunnel/commit/98b1feda82.3.0-beta
[improve][connector][fake] supports setting the number of split rows and reading interval (#3098)https://github.com/apache/seatunnel/commit/efabe6af72.3.0-beta
[feature][connector][fake] Support mutil splits for fake source connector (#2974)https://github.com/apache/seatunnel/commit/c28c44b7c2.3.0-beta
[E2E][ST-Engine] Add test data consistency in 3 node cluster and fix bug (#3038)https://github.com/apache/seatunnel/commit/97400a6f12.3.0-beta
[Improve][all] change Log to @Slf4j (#3001)https://github.com/apache/seatunnel/commit/6016100f12.3.0-beta
[Improve][Connector-V2] Improve fake source connector (#2944)https://github.com/apache/seatunnel/commit/044f62ef32.3.0-beta
[Improve][Connector-v2-Fake]Supports direct definition of data values(row) (#2839)https://github.com/apache/seatunnel/commit/b7d9dde6c2.3.0-beta
[Connector-V2][ElasticSearch] Fix ElasticSearch Connector V2 Bug (#2817)https://github.com/apache/seatunnel/commit/2fcbbf4642.2.0-beta
[DEV][Api] Replace SeaTunnelContext with JobContext and remove singleton pattern (#2706)https://github.com/apache/seatunnel/commit/cbf82f7552.2.0-beta
[Bug][connector-fake] Fake date calculation error(#2573)https://github.com/apache/seatunnel/commit/9ea01298f2.2.0-beta
[Bug][ConsoleSinkV2]fix fieldToString StackOverflow and add Unit-Test (#2545)https://github.com/apache/seatunnel/commit/6f87094562.2.0-beta
[chore][connector-common] Rename SeatunnelSchema to SeaTunnelSchema (#2538)https://github.com/apache/seatunnel/commit/7dc2a27382.2.0-beta
[Imporve][Fake-Connector-V2]support user-defined-schmea and random data for fake-table (#2406)https://github.com/apache/seatunnel/commit/a5447528c2.2.0-beta
[api-draft][Optimize] Optimize module name (#2062)https://github.com/apache/seatunnel/commit/f79e3112b2.2.0-beta