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# Extracción de datos de su catálogo de AWS Glue datos para el análisis de llamadas del SDK de Amazon Chime
<a name="ca-data-model-queries"></a>

Utilice estas consultas de ejemplo para extraer y organizar los datos de su catálogo de datos de Glue para análisis de llamadas de Amazon Chime SDK. 

**nota**  
Para obtener información sobre cómo conectarse a Amazon Athena y consultar el catálogo de datos de Glue, consulte [Conexión a Amazon Athena con ODBC](https://docs.aws.amazon.com/athena/latest/ug/connect-with-odbc.html).

Amplíe cada sección según sea necesario.

## Extraer valores de los metadatos (tipo de datos STRING) de la tabla call\$1analytics\$1metadata
<a name="qry-insights-metadata"></a>

`call_analytics_metadata` tiene el campo `metadata` en formato de cadena JSON. Utilice la función [json\$1extract\$1scalar](https://docs.aws.amazon.com/athena/latest/ug/extracting-data-from-JSON.html) de Athena para consultar los elementos de esta cadena.

```
SELECT
    json_extract_scalar(metadata,'$.voiceConnectorId') AS "VoiceConnector ID",
    json_extract_scalar(metadata,'$.fromNumber') AS "From Number",
    json_extract_scalar(metadata,'$.toNumber') AS "To Number",
    json_extract_scalar(metadata,'$.callId') AS "Call ID",
    json_extract_scalar(metadata,'$.direction') AS Direction,
    json_extract_scalar(metadata,'$.transactionId') AS "Transaction ID"
FROM 
    "GlueDatabaseName"."call_analytics_metadata"
```

## Consultando SIPRECMetadata las actualizaciones en la tabla call\$1analytics\$1metadata
<a name="qry-insights-siprec-metadata"></a>

El `call_analytics_metadata` campo tiene el campo de metadatos en formato de cadena JSON. `metadata`tiene otro objeto anidado denominado`oneTimeMetadata`, este objeto contiene SIPRec metadatos en formato XML original y JSON transformado. Utilice la función `json_extract_scalar` de Athena para consultar los elementos de esta cadena.

```
SELECT
    json_extract_scalar(metadata,'$.voiceConnectorId') AS "VoiceConnector ID",
    json_extract_scalar(metadata,'$.fromNumber') AS "From Number",
    json_extract_scalar(metadata,'$.toNumber') AS "To Number",
    json_extract_scalar(metadata,'$.callId') AS "Call ID",
    json_extract_scalar(metadata,'$.direction') AS Direction,
    json_extract_scalar(metadata,'$.transactionId') AS "Transaction ID",
    json_extract_scalar(json_extract_scalar(metadata,'$.oneTimeMetadata'),'$.siprecMetadata') AS "siprec Metadata XML",
    json_extract_scalar(json_extract_scalar(metadata,'$.oneTimeMetadata'),'$.siprecMetadataJson') AS "Siprec Metadata JSON",
    json_extract_scalar(json_extract_scalar(metadata,'$.oneTimeMetadata'),'$.inviteHeaders') AS "Invite Headers"
FROM 
    "GlueDatabaseName"."call_analytics_metadata"
WHERE 
    callevent-type = "update";
```

## Extraer valores de los metadatos (tipo de datos CADENA) de la tabla call\$1analytics\$1recording\$1metadata
<a name="qry-recording-metadata"></a>

`call_analytics_recording_metadata` tiene el campo de metadatos en formato de cadena JSON. Utilice la función [json\$1extract\$1scalar](https://docs.aws.amazon.com/athena/latest/ug/extracting-data-from-JSON.html) de Athena para consultar los elementos de esta cadena.

```
SELECT
    json_extract_scalar(metadata,'$.voiceConnectorId') AS "VoiceConnector ID",
    json_extract_scalar(metadata,'$.fromNumber') AS "From Number",
    json_extract_scalar(metadata,'$.toNumber') AS "To Number",
    json_extract_scalar(metadata,'$.callId') AS "Call ID",
    json_extract_scalar(metadata,'$.direction') AS Direction,
    json_extract_scalar(metadata,'$.transactionId') AS "Transaction ID"
FROM 
    "GlueDatabaseName"."call_analytics_recording_metadata"
WHERE 
    detail-subtype = "Recording"
```

## Extraer valores de los detalles (tipo de datos STRUCT) de la tabla voice\$1analytics\$1status
<a name="qry-va-status"></a>

`voice_analytics_status` tiene un campo de detalles en el tipo de datos `struct`. En el siguiente ejemplo, se muestra cómo consultar un campo de tipo de datos `struct`:

```
SELECT
    detail.transactionId AS "Transaction ID",
    detail.voiceConnectorId AS "VoiceConnector ID",
    detail.siprecmetadata AS "Siprec Metadata",
    detail.inviteheaders AS "Invite Headers",
    detail.streamStartTime AS "Stream Start Time"
FROM 
    "GlueDatabaseName"."voice_analytics_status"
```

## Unir las tablas voice\$1analytics\$1status y call\$1analytics\$1metadata
<a name="qry-join-va-meta"></a>

En el siguiente ejemplo de consulta, se unen `call_analytics_metadata` y `voice_analytics_status`:

```
SELECT
    a.detail.transactionId AS "Transaction ID",
    a.detail.voiceConnectorId AS "VoiceConnector ID",
    a.detail.siprecmetadata AS "Siprec Metadata",
    a.detail.inviteheaders AS "Invite Headers",
    a.detail.streamStartTime AS "Stream Start Time"
    json_extract_scalar(b.metadata,'$.fromNumber') AS "From Number",
    json_extract_scalar(b.metadata,'$.toNumber') AS "To Number",
    json_extract_scalar(b.metadata,'$.callId') AS "Call ID",
    json_extract_scalar(b.metadata,'$.direction') AS Direction
FROM 
    "GlueDatabaseName"."voice_analytics_status" a
INNER JOIN 
    "GlueDatabaseName"."call_analytics_metadata" b
ON a.detail.transactionId = json_extract_scalar(b.metadata,'$.transactionId')
```

## Extraer transcripciones de la tabla transcribe\$1call\$1analytics\$1post\$1call
<a name="qry-transcribe-ca-post-call"></a>

transcribe\$1call\$1analytics\$1post\$1call has transcript field in struct format with nested arrays. Use la siguiente consulta para separar las matrices:

```
SELECT 
    jobstatus,
    languagecode,
    IF(CARDINALITY(m.transcript)=0 OR CARDINALITY(m.transcript) IS NULL, NULL, e.transcript.id) AS utteranceId,
    IF(CARDINALITY(m.transcript)=0 OR CARDINALITY(m.transcript) IS NULL, NULL, e.transcript.content) AS transcript,
    accountid,
    channel,
    sessionid,
    contentmetadata.output AS "Redaction"
FROM 
    "GlueDatabaseName"."transcribe_call_analytics_post_call" m
CROSS JOIN UNNEST
    (IF(CARDINALITY(m.transcript)=0, ARRAY[NULL], transcript)) AS e(transcript)
```

## Joining the transcribe\$1call\$1analytics\$1post\$1call and call\$1analytics\$1metadata tables
<a name="qry-va-status"></a>

La siguiente consulta permite unirse a las tablas transcribe\$1call\$1analytics\$1post\$1call y call\$1analytics\$1metadata:

```
WITH metadata AS(
  SELECT 
    from_iso8601_timestamp(time) AS "Timestamp",
    date_parse(date_format(from_iso8601_timestamp(time), '%m/%d/%Y %H:%i:%s') , '%m/%d/%Y %H:%i:%s') AS "DateTime",
    date_parse(date_format(from_iso8601_timestamp(time) , '%m/%d/%Y') , '%m/%d/%Y') AS "Date",
    date_format(from_iso8601_timestamp(time) , '%H:%i:%s')  AS "Time",
    mediainsightspipelineid,
    json_extract_scalar(metadata,'$.toNumber') AS "To Number",
    json_extract_scalar(metadata,'$.voiceConnectorId') AS "VoiceConnector ID",
    json_extract_scalar(metadata,'$.fromNumber') AS "From Number",
    json_extract_scalar(metadata,'$.callId') AS "Call ID",
    json_extract_scalar(metadata,'$.direction') AS Direction,
    json_extract_scalar(metadata,'$.transactionId') AS "Transaction ID",
    REGEXP_REPLACE(REGEXP_EXTRACT(json_extract_scalar(metadata,'$.oneTimeMetadata.s3RecordingUrl'), '[^/]+(?=\.[^.]+$)'), '\.wav$', '') AS "SessionID"
  FROM 
    "GlueDatabaseName"."call_analytics_metadata"
),
transcript_events AS(
  SELECT 
    jobstatus,
    languagecode,
    IF(CARDINALITY(m.transcript)=0 OR CARDINALITY(m.transcript) IS NULL, NULL, e.transcript.id) AS utteranceId,
    IF(CARDINALITY(m.transcript)=0 OR CARDINALITY(m.transcript) IS NULL, NULL, e.transcript.content) AS transcript,
    accountid,
    channel,
    sessionid,
    contentmetadata.output AS "Redaction"
  FROM 
    "GlueDatabaseName"."transcribe_call_analytics_post_call" m
  CROSS JOIN UNNEST
    (IF(CARDINALITY(m.transcript)=0, ARRAY[NULL], transcript)) AS e(transcript)
)
SELECT 
    jobstatus,
    languagecode,
    a.utteranceId,
    transcript,
    accountid,
    channel,
    a.sessionid,
    "Redaction"
    "Timestamp",
    "DateTime",
    "Date",
    "Time",
    mediainsightspipelineid,
    "To Number",
    "VoiceConnector ID",
    "From Number",
    "Call ID",
    Direction,
    "Transaction ID"
FROM 
    "GlueDatabaseName"."transcribe_call_analytics_post_call" a
LEFT JOIN 
    metadata b
ON 
    a.sessionid = b.SessionID
```

## Consultando un objeto multimedia URLs para la grabación de llamadas con mejora de voz
<a name="qry-voice-enhancement-call-recording"></a>

El siguiente ejemplo de consulta une la URL `Voice enhancement call recording`:

```
SELECT 
    json_extract_scalar(metadata,'$.voiceConnectorId') AS "VoiceConnector ID",
    json_extract_scalar(metadata,'$.fromNumber') AS "From Number",
    json_extract_scalar(metadata,'$.toNumber') AS "To Number",
    json_extract_scalar(metadata,'$.callId') AS "Call ID",
    json_extract_scalar(metadata,'$.direction') AS Direction,
    json_extract_scalar(metadata,'$.transactionId') AS "Transaction ID",
    s3MediaObjectConsoleUrl
FROM
    {GlueDatabaseName}."call_analytics_recording_metadata"
WHERE
    detail-subtype = "VoiceEnhancement"
```