Sizing TREX70710 ERecruit

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    SIZING GUI ELINE

    Sizing TREX 7.0 and TREX 7.10 forSAP E-Recruiting using Search Engine Service(SES)

    Released for SAP Customers and PartnersDocument Version 1.0, November, 2008

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    Agenda

    1. Introduction

    1.1. Functions and Requirements: Search Functionality Used by SAP E-Recruiting

    1.2. Prerequisites

    1.3. Architecture of SAP E-Recruiting Using Search and Classification TREX

    with Search Engine Service (SES)

    1.4. TREX Landscape

    1.5. Factors that Influence Performance

    2. Sizing TREX 7.0 and TREX 7.10 for SAP E-Recruit ing using SES

    2.1. Sizing Procedure

    2.2. Sizing Guideline

    2.3. Further Information

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    1.1. Functions and Requirements: Search

    Functionality Used by SAP E-Recruiting

    SAP E-Recruiting uses SAPs own search engine Search and Classification (TREX) forsearch functions. Search functionality comprises full text search as well as attribute search.

    Main scenarios for usage of search functionality within SAP E-Recruiting are:

    Recruiter searches for suitable candidates for a requisition.

    Following data can be used for the search:

    Structured data like education, job experience, and so on (depending onthe Customizing settings, attribute search and/or full text search is possible)

    Questionnaires (only attribute search is possible)

    Full text search in attachments (for example, resumes, certificates)

    Internal/external candidate searches for suitable job postings.

    Following data are available for the search:

    Structured data like functional area, contract type, and so on (depending on theCustomizing settings, attribute search and/or full text search is possible)

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    1.2. Prerequisites

    Search Engine Service (SES) is used as an interface to TREX.

    A prerequisite is that Business Function HCM_ERC_SES_1 (delivered with SAP

    enhancement package 3) has to be activated for SAP E-Recruiting (see SAP Note1098046 BF HCM_ERC_SES_1: Enhancements of the search function).

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    1.3. Architecture of SAP E-Recruiting Using

    Search and ClassificationTREX (1)

    The following image illustrates the communication between SAP E-Recruiting and Search andClassification TREX:

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    1.3. Architecture of SAP E-Recruiting using

    Search and ClassificationTREX (2)

    Structured Data of E-Recruit ing Objects:

    For indexing and searching structured data (i.e. data saved in corresponding infotypes

    of E-Recruiting objects such as candidate, requisition, and so on) Search Engine

    Service (SES) is used as an interface to TREX. For each searchable object type, anSES business object must exist.

    The following SES business objects exist in the standard SAP E-Recruiting system forE-Recruiting object types:

    TREX creates the indices for each SES business object as well as the required indices

    for the relationships between the SES business objects and the relevant indexinformation.

    INT_POER/NC SES Business Object Internal PublicationInternal Publication

    EXT_POST/NC SES Business Object External PublicationExternal PublicationERC_REQ/NB SES Business Object RequisitionRequisition

    ERC_CDCY/NE SES Business Object CandidacyCandidacy

    ERC_CAND/NA SES Business Object CandidateCandidate

    SES Business ObjectsE-Recruiting

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    1.3. Architecture of SAP E-Recruiting Using

    Search and ClassificationTREX (3)

    Questionnaires:

    Questionnaires that are used in E-Recruiting are documents of theAppraisal Evaluationand Survey Engine (AES). For documents of the AES engine, SES search can be used.

    The following SES business object exists in the standard SAP E-Recruiting system forquestionnaires used in E-Recruiting:

    Unstructured data:

    The system saves unstructured data such as resumes, certificates, and so on in a

    content repository. The unstructured data is managed by Knowledge Provider (KPro).

    KPro triggers the indexing process for the unstructured data and also supports the

    creation of an index for the unstructured data in the TREX system.

    Unstructured data in E-Recruiting means the attachment documents (for example,resumes) belonging to candidates, candidacies, or requisitions.

    AES_DOC/00000100 SES business object for Documents of the AES EngineQuestionnaires

    SES Business ObjectE-Recruiting

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    1.4. TREX Landscape

    Distributed TREX Landscape:

    Document Index (KPro) may be split if the index is too big to reside on one host.

    SES indexes cannot be split but may reside on different hosts.

    In TREX 7.0, the size of an Index Server Process is limited to 2 GB (due to 32 BitTechnology), thus several Index Servers might be required on each host.

    In TREX 7.1, the size of an Index Server Process is not limited to 2 GB (due to 64 Bittechnology), thus only one Index Server is required on each host.

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    1.5. Factors that Influence Performance

    For sizing TREX for E-Recruiting the following factors have to be taken into account:

    Number and size of indexes (SES indexes + KPro Index) with size of indexes depending on

    corresponding data volume (for example, number of candidates, number of requisitions, andso on).

    Number of attributes per index

    SES indexes:

    Number of attributes is dependent on Customizing of search profiles for correspondingE-Recruiting objects

    Number of attributes for questionnaires is fixed

    KPro index: Number of attributes for attachments is fixed

    TREX Landscape

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    Past experience shows that CPU is usually sufficient for TREX sizing and it is the memoryrequirements that are the decisive limiting factor depending on the amount of data. Thus thesizing is based on the indexing of data in TREX, thereby measuring main memory and diskspace requirements.

    As already outlined in 1.5 Factors that Influence Performance, the number of attributes perindex (SES indexes, KPro index) is a relevant factor for sizing. For the sizing estimations, ascenario with the following numbers of TREX index attributes was used:

    SES indexes:

    ERC_CAND: 65

    ERC_CDCY: 7

    ERC_REQ: 18

    INT_POER: 42

    Document Index (KPro):

    22 attributes

    Note:If the real number of attributes is much larger than the numbers listed here, the main memoryand/or disk space requirements calculated with the sizing formulas (see 2.2 Sizing Guideline)might be too small.

    2.1. Sizing Procedure (1)

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    2.1. Sizing Procedure (2)

    The sizing formulas outlined in 2.2. Sizing Guideline are linear equations since measurementswith up to 140,000 candidates (real data) showed an exact linear behavior.

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    2.2. Sizing Guideline: Input Parameters for

    Sizing Formulas (1)

    Defini tion of Input Parameters :

    SES Indexes:

    Number of candidate questionnaires (AES_DOC/00000100)F

    Number of candidacy questionnaires (AES_DOC/00000100)G

    Number of questionnaires attached to applications (AES_DOC/00000100)H

    Number of released external publications (EXT_POST/NC)E

    Number of released internal publications (INT_POERC/NC)D

    Number of requisitions (ERC_REQ/NB)C

    Number of candidacies with status In Process (ERC_CDCY/NE)B

    Number of candidates (ERC_CAND/NA)A

    Variable Semantics (related SES business object / E-Recruit ing

    object in parenthesis)

    Variable Name

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    2.2. Sizing Guideline: Input Parameters for

    Sizing Formulas (2)

    Document Index (KPro)

    TREX Landscape

    Number of requisition attachments (KPro index)M

    Number of candidacy attachments (KPro index)L

    Number of candidate attachments (KPro index)K

    Variable SemanticsVariable Name

    Number of TREX index servers in the TREX landscapeN

    Variable SemanticsVariable Name

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    2.2. Sizing Guideline: TREX Sizing Disk

    Space Requirements

    Disk space requirements (results in KB):The estimated disk space requirements are the sum of specially weighted input parameters forSES Indexes and Document Index (KPro) plus estimated requirements for queue server.

    SES Indexes

    Ds1 = 3,2 * A

    Ds2 = 0,7 * B

    Ds3 = 1,4 * C

    Ds4 = 8,4 * (D + E)

    Ds5 = 2,4 * (F + G + H)

    Document Index (KPro)

    Ds6 = 22 * (K + L + M)

    Queue Server (peak usage)

    Ds7 = 61 * (K + L + M)

    Total Disk Space [KB] = Ds1 + Ds2 + + Ds7

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    2.3. Further Information

    SAP Notes:

    1173518 TREX 7.0 / 7.10 Sizing for E-Recruiting with SES

    1098046 BF HCM_ERC_SES_1: Enhancements of the search function

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    Thank you!

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