{
    "mode": "man",
    "parameter": "CREATE_AGGREGATE",
    "section": "7",
    "url": "https://www.chedong.com/phpMan.php/man/CREATE_AGGREGATE/7/json",
    "generated": "2026-07-05T16:04:22Z",
    "synopsis": "CREATE [ OR REPLACE ] AGGREGATE name ( [ argmode ] [ argname ] argdatatype [ , ... ] ) (\nSFUNC = sfunc,\nSTYPE = statedatatype\n[ , SSPACE = statedatasize ]\n[ , FINALFUNC = ffunc ]\n[ , FINALFUNCEXTRA ]\n[ , FINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , COMBINEFUNC = combinefunc ]\n[ , SERIALFUNC = serialfunc ]\n[ , DESERIALFUNC = deserialfunc ]\n[ , INITCOND = initialcondition ]\n[ , MSFUNC = msfunc ]\n[ , MINVFUNC = minvfunc ]\n[ , MSTYPE = mstatedatatype ]\n[ , MSSPACE = mstatedatasize ]\n[ , MFINALFUNC = mffunc ]\n[ , MFINALFUNCEXTRA ]\n[ , MFINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , MINITCOND = minitialcondition ]\n[ , SORTOP = sortoperator ]\n[ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ]\n)\nCREATE [ OR REPLACE ] AGGREGATE name ( [ [ argmode ] [ argname ] argdatatype [ , ... ] ]\nORDER BY [ argmode ] [ argname ] argdatatype [ , ... ] ) (\nSFUNC = sfunc,\nSTYPE = statedatatype\n[ , SSPACE = statedatasize ]\n[ , FINALFUNC = ffunc ]\n[ , FINALFUNCEXTRA ]\n[ , FINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , INITCOND = initialcondition ]\n[ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ]\n[ , HYPOTHETICAL ]\n)\nor the old syntax\nCREATE [ OR REPLACE ] AGGREGATE name (\nBASETYPE = basetype,\nSFUNC = sfunc,\nSTYPE = statedatatype\n[ , SSPACE = statedatasize ]\n[ , FINALFUNC = ffunc ]\n[ , FINALFUNCEXTRA ]\n[ , FINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , COMBINEFUNC = combinefunc ]\n[ , SERIALFUNC = serialfunc ]\n[ , DESERIALFUNC = deserialfunc ]\n[ , INITCOND = initialcondition ]\n[ , MSFUNC = msfunc ]\n[ , MINVFUNC = minvfunc ]\n[ , MSTYPE = mstatedatatype ]\n[ , MSSPACE = mstatedatasize ]\n[ , MFINALFUNC = mffunc ]\n[ , MFINALFUNCEXTRA ]\n[ , MFINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , MINITCOND = minitialcondition ]\n[ , SORTOP = sortoperator ]\n)",
    "sections": {
        "NAME": {
            "content": "CREATEAGGREGATE - define a new aggregate function\n",
            "subsections": []
        },
        "SYNOPSIS": {
            "content": "CREATE [ OR REPLACE ] AGGREGATE name ( [ argmode ] [ argname ] argdatatype [ , ... ] ) (\nSFUNC = sfunc,\nSTYPE = statedatatype\n[ , SSPACE = statedatasize ]\n[ , FINALFUNC = ffunc ]\n[ , FINALFUNCEXTRA ]\n[ , FINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , COMBINEFUNC = combinefunc ]\n[ , SERIALFUNC = serialfunc ]\n[ , DESERIALFUNC = deserialfunc ]\n[ , INITCOND = initialcondition ]\n[ , MSFUNC = msfunc ]\n[ , MINVFUNC = minvfunc ]\n[ , MSTYPE = mstatedatatype ]\n[ , MSSPACE = mstatedatasize ]\n[ , MFINALFUNC = mffunc ]\n[ , MFINALFUNCEXTRA ]\n[ , MFINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , MINITCOND = minitialcondition ]\n[ , SORTOP = sortoperator ]\n[ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ]\n)\n\nCREATE [ OR REPLACE ] AGGREGATE name ( [ [ argmode ] [ argname ] argdatatype [ , ... ] ]\nORDER BY [ argmode ] [ argname ] argdatatype [ , ... ] ) (\nSFUNC = sfunc,\nSTYPE = statedatatype\n[ , SSPACE = statedatasize ]\n[ , FINALFUNC = ffunc ]\n[ , FINALFUNCEXTRA ]\n[ , FINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , INITCOND = initialcondition ]\n[ , PARALLEL = { SAFE | RESTRICTED | UNSAFE } ]\n[ , HYPOTHETICAL ]\n)\n\nor the old syntax\n\nCREATE [ OR REPLACE ] AGGREGATE name (\nBASETYPE = basetype,\nSFUNC = sfunc,\nSTYPE = statedatatype\n[ , SSPACE = statedatasize ]\n[ , FINALFUNC = ffunc ]\n[ , FINALFUNCEXTRA ]\n[ , FINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , COMBINEFUNC = combinefunc ]\n[ , SERIALFUNC = serialfunc ]\n[ , DESERIALFUNC = deserialfunc ]\n[ , INITCOND = initialcondition ]\n[ , MSFUNC = msfunc ]\n[ , MINVFUNC = minvfunc ]\n[ , MSTYPE = mstatedatatype ]\n[ , MSSPACE = mstatedatasize ]\n[ , MFINALFUNC = mffunc ]\n[ , MFINALFUNCEXTRA ]\n[ , MFINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE } ]\n[ , MINITCOND = minitialcondition ]\n[ , SORTOP = sortoperator ]\n)\n",
            "subsections": []
        },
        "DESCRIPTION": {
            "content": "CREATE AGGREGATE defines a new aggregate function.  CREATE OR REPLACE AGGREGATE will either\ndefine a new aggregate function or replace an existing definition. Some basic and\ncommonly-used aggregate functions are included with the distribution; they are documented in\nSection 9.21. If one defines new types or needs an aggregate function not already provided,\nthen CREATE AGGREGATE can be used to provide the desired features.\n\nWhen replacing an existing definition, the argument types, result type, and number of direct\narguments may not be changed. Also, the new definition must be of the same kind (ordinary\naggregate, ordered-set aggregate, or hypothetical-set aggregate) as the old one.\n\nIf a schema name is given (for example, CREATE AGGREGATE myschema.myagg ...) then the\naggregate function is created in the specified schema. Otherwise it is created in the current\nschema.\n\nAn aggregate function is identified by its name and input data type(s). Two aggregates in the\nsame schema can have the same name if they operate on different input types. The name and\ninput data type(s) of an aggregate must also be distinct from the name and input data type(s)\nof every ordinary function in the same schema. This behavior is identical to overloading of\nordinary function names (see CREATE FUNCTION (CREATEFUNCTION(7))).\n\nA simple aggregate function is made from one or two ordinary functions: a state transition\nfunction sfunc, and an optional final calculation function ffunc. These are used as follows:\n\nsfunc( internal-state, next-data-values ) ---> next-internal-state\nffunc( internal-state ) ---> aggregate-value\n\nPostgreSQL creates a temporary variable of data type stype to hold the current internal state\nof the aggregate. At each input row, the aggregate argument value(s) are calculated and the\nstate transition function is invoked with the current state value and the new argument\nvalue(s) to calculate a new internal state value. After all the rows have been processed, the\nfinal function is invoked once to calculate the aggregate's return value. If there is no\nfinal function then the ending state value is returned as-is.\n\nAn aggregate function can provide an initial condition, that is, an initial value for the\ninternal state value. This is specified and stored in the database as a value of type text,\nbut it must be a valid external representation of a constant of the state value data type. If\nit is not supplied then the state value starts out null.\n\nIf the state transition function is declared “strict”, then it cannot be called with null\ninputs. With such a transition function, aggregate execution behaves as follows. Rows with\nany null input values are ignored (the function is not called and the previous state value is\nretained). If the initial state value is null, then at the first row with all-nonnull input\nvalues, the first argument value replaces the state value, and the transition function is\ninvoked at each subsequent row with all-nonnull input values. This is handy for implementing\naggregates like max. Note that this behavior is only available when statedatatype is the\nsame as the first argdatatype. When these types are different, you must supply a nonnull\ninitial condition or use a nonstrict transition function.\n\nIf the state transition function is not strict, then it will be called unconditionally at\neach input row, and must deal with null inputs and null state values for itself. This allows\nthe aggregate author to have full control over the aggregate's handling of null values.\n\nIf the final function is declared “strict”, then it will not be called when the ending state\nvalue is null; instead a null result will be returned automatically. (Of course this is just\nthe normal behavior of strict functions.) In any case the final function has the option of\nreturning a null value. For example, the final function for avg returns null when it sees\nthere were zero input rows.\n\nSometimes it is useful to declare the final function as taking not just the state value, but\nextra parameters corresponding to the aggregate's input values. The main reason for doing\nthis is if the final function is polymorphic and the state value's data type would be\ninadequate to pin down the result type. These extra parameters are always passed as NULL (and\nso the final function must not be strict when the FINALFUNCEXTRA option is used), but\nnonetheless they are valid parameters. The final function could for example make use of\ngetfnexprargtype to identify the actual argument type in the current call.\n\nAn aggregate can optionally support moving-aggregate mode, as described in Section 38.12.1.\nThis requires specifying the MSFUNC, MINVFUNC, and MSTYPE parameters, and optionally the\nMSSPACE, MFINALFUNC, MFINALFUNCEXTRA, MFINALFUNCMODIFY, and MINITCOND parameters. Except\nfor MINVFUNC, these parameters work like the corresponding simple-aggregate parameters\nwithout M; they define a separate implementation of the aggregate that includes an inverse\ntransition function.\n\nThe syntax with ORDER BY in the parameter list creates a special type of aggregate called an\nordered-set aggregate; or if HYPOTHETICAL is specified, then a hypothetical-set aggregate is\ncreated. These aggregates operate over groups of sorted values in order-dependent ways, so\nthat specification of an input sort order is an essential part of a call. Also, they can have\ndirect arguments, which are arguments that are evaluated only once per aggregation rather\nthan once per input row. Hypothetical-set aggregates are a subclass of ordered-set aggregates\nin which some of the direct arguments are required to match, in number and data types, the\naggregated argument columns. This allows the values of those direct arguments to be added to\nthe collection of aggregate-input rows as an additional “hypothetical” row.\n\nAn aggregate can optionally support partial aggregation, as described in Section 38.12.4.\nThis requires specifying the COMBINEFUNC parameter. If the statedatatype is internal, it's\nusually also appropriate to provide the SERIALFUNC and DESERIALFUNC parameters so that\nparallel aggregation is possible. Note that the aggregate must also be marked PARALLEL SAFE\nto enable parallel aggregation.\n\nAggregates that behave like MIN or MAX can sometimes be optimized by looking into an index\ninstead of scanning every input row. If this aggregate can be so optimized, indicate it by\nspecifying a sort operator. The basic requirement is that the aggregate must yield the first\nelement in the sort ordering induced by the operator; in other words:\n\nSELECT agg(col) FROM tab;\n\nmust be equivalent to:\n\nSELECT col FROM tab ORDER BY col USING sortop LIMIT 1;\n\nFurther assumptions are that the aggregate ignores null inputs, and that it delivers a null\nresult if and only if there were no non-null inputs. Ordinarily, a data type's < operator is\nthe proper sort operator for MIN, and > is the proper sort operator for MAX. Note that the\noptimization will never actually take effect unless the specified operator is the “less than”\nor “greater than” strategy member of a B-tree index operator class.\n\nTo be able to create an aggregate function, you must have USAGE privilege on the argument\ntypes, the state type(s), and the return type, as well as EXECUTE privilege on the supporting\nfunctions.\n",
            "subsections": []
        },
        "PARAMETERS": {
            "content": "name\nThe name (optionally schema-qualified) of the aggregate function to create.\n\nargmode\nThe mode of an argument: IN or VARIADIC. (Aggregate functions do not support OUT\narguments.) If omitted, the default is IN. Only the last argument can be marked VARIADIC.\n\nargname\nThe name of an argument. This is currently only useful for documentation purposes. If\nomitted, the argument has no name.\n\nargdatatype\nAn input data type on which this aggregate function operates. To create a zero-argument\naggregate function, write * in place of the list of argument specifications. (An example\nof such an aggregate is count(*).)\n\nbasetype\nIn the old syntax for CREATE AGGREGATE, the input data type is specified by a basetype\nparameter rather than being written next to the aggregate name. Note that this syntax\nallows only one input parameter. To define a zero-argument aggregate function with this\nsyntax, specify the basetype as \"ANY\" (not *). Ordered-set aggregates cannot be defined\nwith the old syntax.\n\nsfunc\nThe name of the state transition function to be called for each input row. For a normal\nN-argument aggregate function, the sfunc must take N+1 arguments, the first being of type\nstatedatatype and the rest matching the declared input data type(s) of the aggregate.\nThe function must return a value of type statedatatype. This function takes the current\nstate value and the current input data value(s), and returns the next state value.\n\nFor ordered-set (including hypothetical-set) aggregates, the state transition function\nreceives only the current state value and the aggregated arguments, not the direct\narguments. Otherwise it is the same.\n\nstatedatatype\nThe data type for the aggregate's state value.\n\nstatedatasize\nThe approximate average size (in bytes) of the aggregate's state value. If this parameter\nis omitted or is zero, a default estimate is used based on the statedatatype. The\nplanner uses this value to estimate the memory required for a grouped aggregate query.\n\nffunc\nThe name of the final function called to compute the aggregate's result after all input\nrows have been traversed. For a normal aggregate, this function must take a single\nargument of type statedatatype. The return data type of the aggregate is defined as the\nreturn type of this function. If ffunc is not specified, then the ending state value is\nused as the aggregate's result, and the return type is statedatatype.\n\nFor ordered-set (including hypothetical-set) aggregates, the final function receives not\nonly the final state value, but also the values of all the direct arguments.\n\nIf FINALFUNCEXTRA is specified, then in addition to the final state value and any direct\narguments, the final function receives extra NULL values corresponding to the aggregate's\nregular (aggregated) arguments. This is mainly useful to allow correct resolution of the\naggregate result type when a polymorphic aggregate is being defined.\n\nFINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE }\nThis option specifies whether the final function is a pure function that does not modify\nits arguments.  READONLY indicates it does not; the other two values indicate that it\nmay change the transition state value. See Notes below for more detail. The default is\nREADONLY, except for ordered-set aggregates, for which the default is READWRITE.\n\ncombinefunc\nThe combinefunc function may optionally be specified to allow the aggregate function to\nsupport partial aggregation. If provided, the combinefunc must combine two\nstatedatatype values, each containing the result of aggregation over some subset of the\ninput values, to produce a new statedatatype that represents the result of aggregating\nover both sets of inputs. This function can be thought of as an sfunc, where instead of\nacting upon an individual input row and adding it to the running aggregate state, it adds\nanother aggregate state to the running state.\n\nThe combinefunc must be declared as taking two arguments of the statedatatype and\nreturning a value of the statedatatype. Optionally this function may be “strict”. In\nthis case the function will not be called when either of the input states are null; the\nother state will be taken as the correct result.\n\nFor aggregate functions whose statedatatype is internal, the combinefunc must not be\nstrict. In this case the combinefunc must ensure that null states are handled correctly\nand that the state being returned is properly stored in the aggregate memory context.\n\nserialfunc\nAn aggregate function whose statedatatype is internal can participate in parallel\naggregation only if it has a serialfunc function, which must serialize the aggregate\nstate into a bytea value for transmission to another process. This function must take a\nsingle argument of type internal and return type bytea. A corresponding deserialfunc is\nalso required.\n\ndeserialfunc\nDeserialize a previously serialized aggregate state back into statedatatype. This\nfunction must take two arguments of types bytea and internal, and produce a result of\ntype internal. (Note: the second, internal argument is unused, but is required for type\nsafety reasons.)\n\ninitialcondition\nThe initial setting for the state value. This must be a string constant in the form\naccepted for the data type statedatatype. If not specified, the state value starts out\nnull.\n\nmsfunc\nThe name of the forward state transition function to be called for each input row in\nmoving-aggregate mode. This is exactly like the regular transition function, except that\nits first argument and result are of type mstatedatatype, which might be different from\nstatedatatype.\n\nminvfunc\nThe name of the inverse state transition function to be used in moving-aggregate mode.\nThis function has the same argument and result types as msfunc, but it is used to remove\na value from the current aggregate state, rather than add a value to it. The inverse\ntransition function must have the same strictness attribute as the forward state\ntransition function.\n\nmstatedatatype\nThe data type for the aggregate's state value, when using moving-aggregate mode.\n\nmstatedatasize\nThe approximate average size (in bytes) of the aggregate's state value, when using\nmoving-aggregate mode. This works the same as statedatasize.\n\nmffunc\nThe name of the final function called to compute the aggregate's result after all input\nrows have been traversed, when using moving-aggregate mode. This works the same as ffunc,\nexcept that its first argument's type is mstatedatatype and extra dummy arguments are\nspecified by writing MFINALFUNCEXTRA. The aggregate result type determined by mffunc or\nmstatedatatype must match that determined by the aggregate's regular implementation.\n\nMFINALFUNCMODIFY = { READONLY | SHAREABLE | READWRITE }\nThis option is like FINALFUNCMODIFY, but it describes the behavior of the\nmoving-aggregate final function.\n\nminitialcondition\nThe initial setting for the state value, when using moving-aggregate mode. This works the\nsame as initialcondition.\n\nsortoperator\nThe associated sort operator for a MIN- or MAX-like aggregate. This is just an operator\nname (possibly schema-qualified). The operator is assumed to have the same input data\ntypes as the aggregate (which must be a single-argument normal aggregate).\n\nPARALLEL = { SAFE | RESTRICTED | UNSAFE }\nThe meanings of PARALLEL SAFE, PARALLEL RESTRICTED, and PARALLEL UNSAFE are the same as\nin CREATE FUNCTION. An aggregate will not be considered for parallelization if it is\nmarked PARALLEL UNSAFE (which is the default!) or PARALLEL RESTRICTED. Note that the\nparallel-safety markings of the aggregate's support functions are not consulted by the\nplanner, only the marking of the aggregate itself.\n\nHYPOTHETICAL\nFor ordered-set aggregates only, this flag specifies that the aggregate arguments are to\nbe processed according to the requirements for hypothetical-set aggregates: that is, the\nlast few direct arguments must match the data types of the aggregated (WITHIN GROUP)\narguments. The HYPOTHETICAL flag has no effect on run-time behavior, only on parse-time\nresolution of the data types and collations of the aggregate's arguments.\n\nThe parameters of CREATE AGGREGATE can be written in any order, not just the order\nillustrated above.\n",
            "subsections": []
        },
        "NOTES": {
            "content": "In parameters that specify support function names, you can write a schema name if needed, for\nexample SFUNC = public.sum. Do not write argument types there, however — the argument types\nof the support functions are determined from other parameters.\n\nOrdinarily, PostgreSQL functions are expected to be true functions that do not modify their\ninput values. However, an aggregate transition function, when used in the context of an\naggregate, is allowed to cheat and modify its transition-state argument in place. This can\nprovide substantial performance benefits compared to making a fresh copy of the transition\nstate each time.\n\nLikewise, while an aggregate final function is normally expected not to modify its input\nvalues, sometimes it is impractical to avoid modifying the transition-state argument. Such\nbehavior must be declared using the FINALFUNCMODIFY parameter. The READWRITE value\nindicates that the final function modifies the transition state in unspecified ways. This\nvalue prevents use of the aggregate as a window function, and it also prevents merging of\ntransition states for aggregate calls that share the same input values and transition\nfunctions. The SHAREABLE value indicates that the transition function cannot be applied after\nthe final function, but multiple final-function calls can be performed on the ending\ntransition state value. This value prevents use of the aggregate as a window function, but it\nallows merging of transition states. (That is, the optimization of interest here is not\napplying the same final function repeatedly, but applying different final functions to the\nsame ending transition state value. This is allowed as long as none of the final functions\nare marked READWRITE.)\n\nIf an aggregate supports moving-aggregate mode, it will improve calculation efficiency when\nthe aggregate is used as a window function for a window with moving frame start (that is, a\nframe start mode other than UNBOUNDED PRECEDING). Conceptually, the forward transition\nfunction adds input values to the aggregate's state when they enter the window frame from the\nbottom, and the inverse transition function removes them again when they leave the frame at\nthe top. So, when values are removed, they are always removed in the same order they were\nadded. Whenever the inverse transition function is invoked, it will thus receive the earliest\nadded but not yet removed argument value(s). The inverse transition function can assume that\nat least one row will remain in the current state after it removes the oldest row. (When this\nwould not be the case, the window function mechanism simply starts a fresh aggregation,\nrather than using the inverse transition function.)\n\nThe forward transition function for moving-aggregate mode is not allowed to return NULL as\nthe new state value. If the inverse transition function returns NULL, this is taken as an\nindication that the inverse function cannot reverse the state calculation for this particular\ninput, and so the aggregate calculation will be redone from scratch for the current frame\nstarting position. This convention allows moving-aggregate mode to be used in situations\nwhere there are some infrequent cases that are impractical to reverse out of the running\nstate value.\n\nIf no moving-aggregate implementation is supplied, the aggregate can still be used with\nmoving frames, but PostgreSQL will recompute the whole aggregation whenever the start of the\nframe moves. Note that whether or not the aggregate supports moving-aggregate mode,\nPostgreSQL can handle a moving frame end without recalculation; this is done by continuing to\nadd new values to the aggregate's state. This is why use of an aggregate as a window function\nrequires that the final function be read-only: it must not damage the aggregate's state\nvalue, so that the aggregation can be continued even after an aggregate result value has been\nobtained for one set of frame boundaries.\n\nThe syntax for ordered-set aggregates allows VARIADIC to be specified for both the last\ndirect parameter and the last aggregated (WITHIN GROUP) parameter. However, the current\nimplementation restricts use of VARIADIC in two ways. First, ordered-set aggregates can only\nuse VARIADIC \"any\", not other variadic array types. Second, if the last direct parameter is\nVARIADIC \"any\", then there can be only one aggregated parameter and it must also be VARIADIC\n\"any\". (In the representation used in the system catalogs, these two parameters are merged\ninto a single VARIADIC \"any\" item, since pgproc cannot represent functions with more than\none VARIADIC parameter.) If the aggregate is a hypothetical-set aggregate, the direct\narguments that match the VARIADIC \"any\" parameter are the hypothetical ones; any preceding\nparameters represent additional direct arguments that are not constrained to match the\naggregated arguments.\n\nCurrently, ordered-set aggregates do not need to support moving-aggregate mode, since they\ncannot be used as window functions.\n\nPartial (including parallel) aggregation is currently not supported for ordered-set\naggregates. Also, it will never be used for aggregate calls that include DISTINCT or ORDER BY\nclauses, since those semantics cannot be supported during partial aggregation.\n",
            "subsections": []
        },
        "EXAMPLES": {
            "content": "See Section 38.12.\n",
            "subsections": []
        },
        "COMPATIBILITY": {
            "content": "CREATE AGGREGATE is a PostgreSQL language extension. The SQL standard does not provide for\nuser-defined aggregate functions.\n",
            "subsections": []
        },
        "SEE ALSO": {
            "content": "ALTER AGGREGATE (ALTERAGGREGATE(7)), DROP AGGREGATE (DROPAGGREGATE(7))\n\n\n\nPostgreSQL 14.23                                2026                             CREATE AGGREGATE(7)",
            "subsections": []
        }
    },
    "summary": "CREATEAGGREGATE - define a new aggregate function",
    "flags": [],
    "examples": [
        "See Section 38.12."
    ],
    "see_also": [
        {
            "name": "ALTERAGGREGATE",
            "section": "7",
            "url": "https://www.chedong.com/phpMan.php/man/ALTERAGGREGATE/7/json"
        },
        {
            "name": "DROPAGGREGATE",
            "section": "7",
            "url": "https://www.chedong.com/phpMan.php/man/DROPAGGREGATE/7/json"
        },
        {
            "name": "AGGREGATE",
            "section": "7",
            "url": "https://www.chedong.com/phpMan.php/man/AGGREGATE/7/json"
        }
    ]
}