How do I know that Homesharing is working - without waiting for hours to check destination device?

How do I know or can tell that Homesharing is working between iTune devices without having to wait some time to check the destination device?

1. How does the client device know which Airport to connect to?
The Mac computer will automatically connect to the wireless access point with the strongest signal...which is probably the closest AirPort. An iPhone or iPad may not do this and will tend to stay connected to one AirPort.
2. How can I tell which of the Airports the attached client device is using?
On a Mac, open Macintosh HD > Applications > Utilities > AirPort Utility. Click on one of AirPorts. In the area to the right, locate the AirPort ID and jot that down. Then do the same for your other AirPort.
Move your Mac near one of the AirPorts and log on to the wireless. Hold down the option key on the Mac while you click the fan shaped AirPort icon at the top of the screen. Look for the BSSID. That is the AirPort ID of the device to which you are connected.
If you are close to the "remote" AirPort, and you see the AIrPort ID of the "main" router when you are testing, then you know that the network is not configured correctly.
Can I use this second Airport Express to extend the wireless network via "Extended Wireless Network" while the other two are in "Roaming Netowrk" configuration? Without bogging down??
There will be a modest 10-15% bandwidth loss with the "extend" setup, assuming that the Express is located where it can receive a strong wireless signal from the AirPort to which it is associated. You can avoid the bandwidth loss if the Express is also connected via Ethernet as part of the roaming configuration.

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         When compared to a fact table, dimensions ideally have a small cardinality. However, there is an exception to this rule. For example, there are InfoCubes in which a characteristic Document is used, in which case almost every entry in the fact table is assigned to a different Document. This means that the dimension (or the associated dimension table) has almost as many entries as the fact table itself. We refer here to a degenerated dimension.
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           When loading transaction data, no IDs are generated for the entries in the dimension table. This number range operation can compromise performance precisely in the case where a degenerated dimension is involved.
          A table- having a very large cardinality- is removed from the star schema. as a result, the SQL-based queries are simpler. In many cases, the database optimizer can choose better execution plans.
    Nevertheless, it also has a disadvantage: A dimension marked as a line item cannot subsequently include additional characteristics. This is only possible with normal dimensions.
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           2.      High cardinality: This means that the dimension is to have a large number of instances (that is, a high cardinality). This information is used to carry out optimizations on a physical level in depending on the database platform. Different index types are used than is normally the case. A general rule is that a dimension has a high cardinality when the number of dimension entries is at least 20% of the fact table entries. If you are unsure, do not select a dimension having high cardinality.
    Activities
    When creating dimensions in the InfoCube maintenance, flag the relevant dimension as a Line Item/ having High Cardinality.
    Define lots of small dimensions rather than a few large dimensions.
         The size of the dimension tables should account for less than 10% of the fact table.
         If the size of the dimension table amounts to more than 10% of the fact table, mark the dimension as a line item dimension.
    To attain good performance for a query on non-cumulative InfoCubes, you should take note of the following:
    Compression:
    Compress all requests in the non-cumulative InfoCube, or at least most of them.
    The performance of a query based on a non-cumulative InfoCube depends heavily on how the InfoCube is compressed. If you want to improve the performance of a query of this type, first check – in so far as this is possible - whether the data in the InfoCube should be compressed. You should always compress data when you are sure that the request affected will not need to be deleted from the InfoCube.
    Validity Table
    Use as few validity-determining characteristics as possible.
    The number and cardinality of the validity-determining characteristics heavily influences performance. Therefore, you should only define characteristics as validity-determining characteristics when it is really necessary.
    Time Restrictions in the Query
    As far as possible, restrict queries based on non-cumulative InfoCubes to time characteristics.
    The stricter the time-based restriction, the faster the query is generally executed, as the non-cumulative is reconstructed if the number of times is smaller.
    Time Drilldown in the Query
    If you no longer need the average, split a query on a non-cumulative InfoCube (which contains both key figures with LAST aggregation and key figures with AVERAGE aggregation) into two queries.
    With non-cumulative key figures with the exception aggregation LAST, the time characteristic included in the drilldown makes a difference to performance. If, for example, both Calendar Day and Calendar Month are included in the InfoCube, drilldown by month is faster than drilldown by day, because the number of times for which a non-cumulative has to be calculated is smaller.
    For the other types of exception aggregation (average, average weighted with factory calendar, minimum and maximum), this rule is not valid as in these cases, the data is always calculated on the level of the most detailed time characteristic first before exception aggregation is performed.
    Totals Rows
    Hide the totals row in the query when not required.
    Depending on the type of aggregation being used, the calculation of totals rows can be very time-consuming.
    When selecting MDC dimensions, proceed as follows:
            Select dimensions for which you often use restrictions in queries.
            Select dimensions with a low cardinality.
    The MDC dimension is created in the column with the dimension keys (DIMID). The number of different combinations in the dimension characteristics determines the cardinality. Therefore, select a dimension with either one, or few characteristics and with only a few different characteristic values.
    Line item dimensions are not usually suitable, as they normally have a characteristic with a high cardinality.
    If you specifically want to create an MDC dimension for a characteristic with a low cardinality, you can define this characteristic as a line item dimension in the InfoCube. This differs from the norm that line item dimensions contain characteristics with a very high cardinality. However, this has the advantage for multidimensional clustering that the fact table contains the SID values of the characteristic, in place of the dimension keys, and the database query can be restricted to these SID values.
            You cannot select more than three dimensions, including the time dimension.
            Assign sequence numbers, using the following criteria:
            Sort the dimensions according to how often they occur in queries (assign the lowest sequence number to the InfoObject that occurs most often in queries).
            Sort the dimensions according to selectivity (assign the lowest sequence number to the dimension with the most different data records).
    Note: At least one block is created for each value combination in the MDC dimension. This memory area is reserved independently of the number of data records that have the same value combination in the MDC dimension. If there is not a sufficient number of data records with the same value combinations to completely fill a block, the free memory remains unused. This is so that data records with a different value combination in the MDC dimension cannot be written to the block.
    If for each combination that exists in the InfoCube, only a few data records exist in the selected MDC dimension, most blocks have unused free memory. This means that the fact tables use an unnecessarily large amount of memory space. Performance of table queries also deteriorates, as many pages with not much information must be read.
    Example
    The size of a block depends on the PAGESIZE and the EXTENTSIZE of the tablespace. The standard PAGESIZE of the fact-table tablespace with the assigned data class DFACT is 16K. Up to Release SAP BW 3.5, the default EXTENTSIZE value was 16. As of Release SAP NetWeaver 2004s the new default EXTENTSIZE value is 2.
    With an EXTENTSIZE of 2 and a PAGESIZE of 16K the memory area is calculated as 2 x 16K = 32K, this is reserved for each block.
    The width of a data record depends on the number of dimensions and the number of key figures in the InfoCube. A dimension key field uses 4 bytes and a decimal key figure uses 9 bytes. If, for example an InfoCube has 3 standard dimensions, 7 customer dimensions and 30 decimal key figures, a data record needs 10 x 4 bytes + 30 x 9 bytes = 310 bytes. In a 32K block, 32768 bytes / 310 bytes could write 105 data records.
    If the time characteristic calendar month (0CALMONTH) and a customer dimension are selected as the MDC dimension for this InfoCube, at least 100 data records should exist for each InfoPackage, for each calendar month and for each dimension key of the customer dimension. This allows optimal use of the memory space in the F fact table. In the E fact table, this is valid for each calendar month and each dimension key of the customer dimension,dimension contains a characteristic whose value already uniquely determines the values of all other characteristics from a business-orientated viewpoint, then the dimension is named after this characteristic.
      The customer dimension could, for example, be made up of the customer number, the customer group and the levels of the customer hierarchy.
    The sales dimension could contain the characteristics ‘sales person’, ‘sales group’ and ‘sales office’.                                            
    The time dimension could be given using the characteristics ‘day’ (in the form YYYYMMDD), ‘week’ (in the form YYYY.WW), ‘month’ (in the form YYYY.MM), ‘year’ (in the form YYYY) and ‘period’ (in the form YYYY.PPP).
    Use
    When defining an InfoCube, characteristics for dimensions are grouped together to enable them to be stored in a star schema table (dimension table). The aforementioned business-orientated grouping can be the basis for this. With the aid of a simple foreign key dependency, dimensions are linked to one of the key fields of the fact table.
    When you create an InfoCube, the dimensions data package, time and unit are already defined by default. The data package dimension contains technical characteristics. Time characteristics and units are automatically assigned to the corresponding dimensions. When you activate the InfoCube, only those dimensions that contain InfoObjects are activated.
    From a technical viewpoint several characteristic values are mapped to an abstract dimension key (DIM ID), to which the values in the fact table refer. The characteristics chosen for an InfoCube are divided up among InfoCube-specific dimensions when creating the InfoCube.
    Also refer to the following for specific cases arising when defining dimensions:
    Line Item and High Cardinality
    The methods for setting and getting data from a named range use the separation between the description of the range and the data itself. Note that the sequence must be observed both in the range description (structure soi_range_list ) and in the data (structure soi_generic_table ). This means that you must list all data from the first range before you can insert data into the second range.
    Structure soi_range_list
    Field
    Type
    Description
    name
    C
    Name of the range
    rows
    C
    Number of rows
    columns
    C
    Number of columns
    code
    C
    Function in the range:
    SPREADSHEET->SPREADSHEET_CLEAR : Deletes range
    SPREADSHEET->SPREADSHEET_COLUMNSHIDE : Hides columns
    SPREADSHEET->SPREADSHEET_ROWSHIDE : Hides rows
    SPREADSHEET->SPREADSHEET_PROTECT : Range is protected
    SPREADSHEET->SPREADSHEET_UNPROTECT : Range is not protected
    SPREADSHEET->SPREADSHEET_COLUMNSSHOW : Columns are displayed.
    SPREADSHEET->SPREADSHEET_ROWSSHOW : Rows are displayed.
    SPREADSHEET->SPREADSHEET_INSERTALL : The entire table is inserted, regardless of the size of the area
    SPREADSHEET->SPREADSHEET_NEWRANGE : Creates a new range
    The name identifies the range in the worksheet. This is, in effect, the key with which you always access the range. The size of the range is always given in columns and rows.
    Some functions allow you to access a specific area in a worksheet. You can see from the table which functions are implemented.
    Description of Data Type soi_generic_table
    In this table, you can save data from the range and use the  Data Provider to transfer it to or retrieve it from the frontend. The data is transferred directly as a string with no type information.
    Structure soi_generic_table
    Field
    Type
    Description
    row
    C(4)
    Row
    column
    C(4)
    Column
    value
    C(256)
    Value
    The sequence of the data must correspond to the sequence of the range description, for example, range1 before range2 . The data table must then contain the data for the ranges in the sequence range1 range2 .
    Description of Data Type soi_format_table
    Use this table to specify the format of a range. The format consists of various attributes, all of which can be set in a single line. Each variable attribute corresponds to a column of the structure.
    To create a work area for this table, use the structure soi_format_item as a reference.
    The entry "-1" always indicates that the existing attribute value for the range should not be changed.
    Structure soi_format_table
    Field
    Type
    Description
    name
    C(256)
    Name of the range
    front
    I
    Font color (see color palette)
    back
    I
    Background color (see color palette)
    font
    C(256)
    Name of the font family. The following values are permitted:
    'Arial'
    'Courier New'
    'Times New Roman'
    size
    I
    Font size
    '-1' : Unchanged
    bold
    I
    '1' : Bold
    '0' : Normal
    '-1' : Unchanged
    italic
    I
    '1' : Italic
    '0' : Normal
    '-1' : Unchanged
    align
    I
    Alignment:
    '-1' : Unchanged
    '0' : Right-justified
    '1' : Centered
    '2' : Left-justified
    frametype
    I
    Control byte for setting the frame
    '-1' : Unchanged
    framecolor
    I
    Frame color (see color palette)
    '-1' : Unchanged
    currency
    C(3)
    ISO standard currency code
    number
    I
    Specifies the format of a cell in a range.
    1: Display as a simple number
    2: Scientific display
    3: Display as a percentage
    The control byte type contains the following bits. If a bit is set, its corresponding line is drawn. You can set the thickness of the line to one of four levels using bits 6 and 7.
    Bit
    Description
    0
    Sets the left margin
    1
    Sets the top margin
    2
    Sets the bottom margin
    3
    Sets the right margin
    4
    Horizontal line
    5
    Sets the left margin
    6
    Thickness
    7
    Thickness
    Description of Data Type soi_full_range_table
    Each line of a table with the type soi_full_range_table specifies the full definition of a range. The individual lines have the data type soi_full_range_item .
    Structure soi_full_range_table
    Field
    Type
    Description
    name
    C(128)
    Name of the range
    top
    I
    Top row of the range
    left
    I
    Leftmost column of the range
    rows
    I
    Number of rows in the range
    columns
    I
    Number of columns in the range
    sheets
    C(128)
    Worksheet on which the range is defined
    Description of Data Type soi_cell_table
    Each line of a table with the type soi_cell_table specifies the attributes of a range of cells. However, no range name is used. Instead, the cell area is defined by its starting position and the number of rows and columns it contains.The individual lines have the data type soi_cell_item .
    Structure soi_cell_table
    Field
    Type
    Description
    top
    I
    Top row of the range
    left
    I
    Leftmost column of the range
    rows
    I
    Number of rows in the range
    columns
    I
    Number of columns in the range
    front
    I
    Font color (see color palette)
    back
    I
    Background color (see color palette)
    font
    C(256)
    Font. The following are permitted:
    Arial
    Courier New
    Times Roman
    size
    I
    Font size
    Use -1 if the font size is to remain unchanged.
    bold
    I
    '1' : Bold
    '0' : Normal
    '-1' : Unchanged
    italic
    I
    '1' : Italic
    '0' : Normal
    '-1' : Unchanged
    align
    I
    Alignment:
    '-1' : Unchanged
    '0' : Right-justified
    '1' : Centered
    '2' : Left-justified
    frametype
    I
    Control byte for setting the frame
    '-1' : Unchanged
    framecolor
    I
    Frame color (see color palette)
    '-1' : Unchanged
    currency
    C(3)
    ISO standard currency code
    number
    I
    Specifies the format of a cell in a range.
    1: Display as a simple number
    2: Scientific display
    3: Display as a percentage
    decimals
    I
    Number of decimal places
    input
    I
    '0' : Input off
    '1' : Input on
    Description of Data Type soi_dimension_table
    You can use an internal table with this type to identify a range by specifying the coordinates of its top left-hand corner, its length, and its width. The lines of soi_dimension_table have the line type soi_dimension_item .
    Structure soi_dimension_item
    Field
    Type
    Decription
    top
    I
    Topmost row of the range
    left
    I
    Leftmost column of the range
    rows
    I
    Number of rows
    columns
    I
    Number of columns
    Term
    Definition
    Board
    A tabbed area in the workspace used to manipulate the model and its elements: Design board, Layout board and Source board.
    Characteristic
    A type of InfoObject in SAP BI systems that provides a classification such as company code, product, customer group, fiscal year, period, or region. Related to the OLAP-standard term dimension.
    Component
    A reusable model element, such as a UI component or a data service.
    Cube
    A set of data organized as a multidimensional structure defined according to dimensions and measures.
    Related SAP BI terms include InfoCube and query.
    Data binding
    A connection between two UI components (or between a web service and a UI component) that channels identical data from the output port of one UI component to the input port of the other UI component.
    Data flow
    The means by which data is channeled between a data service and connected UI components, or between two UI components whose connection was changed from Data binding to Data flow.
    Data mapping
    Connection between two model elements, describing, for example, the data that is input to an element or the fields that are output from another element.
    Data service
    Any function call, business object or query imported into the model. At runtime, the data service is called and returns results.
    Data store
    A central data container where data of a model can be temporarily stored for future use.
    Dimension
    In OLAP-standard systems:
    A collection of similar data which, together with other such collections, forms the structure of a cube. Typical dimensions include time, product, and geography. Each dimension may be organized into a basic parent-child hierarchy or, if supported by the data source, a hierarchy of levels.  For example, a geography dimension might include levels for continent, country, state, and city.
    The related term in SAP BI systems is characteristic.
    In SAP BI systems:
    A grouping of those evaluation groups (characteristics) that belong together under a common superordinate term.
    With the definition of an InfoCube, characteristics are grouped together into dimensions in order to store them in a star schema table (dimension table).
    Element
    A general term indicating any item used to create a model, including: components, connectors and operators.
    Enterprise service
    A Web service defined to perform functions of an SAP system. Web services are published to and stored within a repository.
    Field
    An element of a table that contains a single piece of data. Fields are organized into rows, which contain all the data relevant for one specific entry in the table.  In some databases, field is a synonym for column.
    Filter
    A set of criteria that restricts the set of records returned as the result of a query. With filters, you define which subset of data appears in the result set.
    Hierarchy
    A logical tree structure that organizes the members of a dimension into a parent-child relationship. If supported by the data source, the hierarchy consists of levels, where the top level is an aggregate of all members and each subsequent level has zero or more child members.
    InfoArea
    An element for grouping meta-objects in the Business Information Warehouse. Each InfoProvider is assigned to an InfoArea. The resulting hierarchy is displayed in the Administrator Workbench.
    InfoCube
    An SAP BI system that consists of a quantity of relational tables created according to the star schema: a large fact table in the center, with several dimension tables surrounding it. It provides a self-contained dataset which can be used for analysis and reporting.
    Similar to the OLAP-standard term cube.
    InfoObject
    A business evaluation object (for example, customer or quantity) in SAP BI systems. Types of InfoObjects include characteristics, key figures, units, time characteristics, and technical characteristics (such as request numbers).
    JDBC
    Java Database Connectivity, which provides an API that lets you access relational databases using the Java programming language. This enables connectivity to a wide range of SQL databases, and also provides access to tabular data sources such as spreadsheets or flat files. The BI JDBC Connector accesses data from JDBC-compliant systems.
    Join
    A relationship between two tables that produces a result set that combines their contents. You create a join by indicating how selected fields in one table are related to selected fields in the other table.
    Key figure
    A value or quantity in SAP BI systems. Related to the OLAP-standard term measure. You may also define calculated key figures, which are derived using a formula.
    Layer
    A collection of UI elements that are all visible at the same time at runtime.
    Level
    A set of nodes (members) in a tree hierarchy in supporting data sources that are at the same distance from the root of the tree. For example, in a geography hierarchy, the top level might be all places, the second level might be continents, the third level might be countries, and the fourth level might be cities.
    MDX
    Multidimensional Expressions, a query language used to retrieve and manipulate multidimensional data.
    Measure
    One category of values – usually numeric – used to define a cube. These values are derived from one or more columns in the cube's fact table and are the basis for aggregation and analysis.
    Related SAP BI terms include key figure and structure element.
    Member
    An element of a dimension that represents one or more occurrences of data. A member can be unique (it occurs only once) or non-unique (it may occur more than once in its dimension).  For example, in a geography dimension that includes cities in the US, the member Portland could be non-unique, since there is a city called Portland in the state of Oregon and in the state of Maine.
    In SAP BI systems, members are referred to as instances of characteristics.
    Model
    An object created in Storyboard. Models may contain packages, pages, iViews and any other model elements.
    Multidimensional data
    Data in dimensional models suitable for business analytics. In this documentation, we use the term multidimensional data synonymously with OLAP data.
    Navigation line
    A connection that provides event annotation, running between model layers. The source element raises the event that can be handled by the connected element. By default, a navigation line is curved.
    ODBO
    OLE DB for OLAP – Microsoft’s set of objects and interfaces that extend the ability of OLE DB to provide access to multidimensional data sources on the Windows platform. Providers of OLAP data can implement the interfaces described with OLE DB for OLAP to allow all OLAP clients to access their data. The BI ODBO Connector accesses data from ODBO-compliant systems.
    OLAP
    Online analytical processing – a system of organizing data in a multidimensional model that is suitable for decision support. SAP BI systems are OLAP systems.
    Operation
    A functionality provided by a Web service.
    Operator
    A mechanism used to manipulate data returned from the data service before it is displayed in the iView.
    Package
    A high-level “container”; it can contain any number of pages, iViews or other packages.
    Port
    A defined point of interface into and out of a component.
    Query
    In SAP BI systems, a collection of selected characteristics and key figures (InfoObjects) used together to analyze the data of an InfoProvider. A query always refers exactly to one InfoProvider, whereas you can define as many queries as you like for each InfoProvider.
    Query view
    In SAP BI systems, a view of a query after navigation, saved in an InfoCube. You can use this saved query view as a basis for data analysis and reporting.
    Relational database
    A repository for typically large amounts of information, structured in accordance with the relational model, in tables with columns. A relational database is created and administered by a relational database management system (RDBMS).
    Row
    A set of fields within a table that contains the data for one specific entry in the table. Each row in a given table has the same structure, predefined for a particular table. In some databases, row is a synonym for record.
    SAP Query
    A component that allows you to create custom reports without any ABAP programming knowledge. The BI SAP Query Connector uses SAP Query to access data from such SAP operational applications.
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