查詢通話記錄

文章
04/24/2024

概觀和存取

在您可充分利用 Log Analytics 以取得通訊服務記錄之前，必須先遵循在診斷設定中啟用記錄中所述的步驟。啟用記錄和 Log Analytics 工作區之後，您就能存取許多實用的預設查詢套件，藉以協助您快速視覺化並瞭解記錄中可用的資料，如下所述。透過 Log Analytics，您也可透過 Azure 監視器 Workbooks 存取更多通訊服務深入解析、建立自己查詢和 Workbook 的能力，並可取得對任何查詢的 Log Analytics 概觀。

存取

您可從 [通訊服務] 資源頁面開始存取查詢，然後按一下 [監視] 區段內左側導覽中的 [記錄]：

Log Analytics 導覽

從這裡，您會看到強制回應畫面，其中包含通訊服務可用的所有預設查詢套件，以及瀏覽左側提供的查詢套件清單。

如果您關閉強制回應畫面，仍可瀏覽至各種查詢套件，並根據您在診斷設定中啟用的記錄和計量結構描述，直接存取資料表形式的資料。在這裡，您可使用 KQL (Kusto) 根據資料建立自己的查詢。若要深入瞭解如何使用、編輯和建立查詢，請參閱：Log Analytics 查詢

通話摘要和通話診斷記錄的預設查詢套件

下列是預設查詢套件中每個查詢的說明 (適用於通話摘要和通話診斷記錄)，其中包含每個可用查詢的程式碼範例和範例輸出：

通話概觀查詢

每個通話的參與者數目

// Count number of calls and participants,
// and print average participants per call
ACSCallSummary
| distinct CorrelationId, ParticipantId, EndpointId
| summarize num_participants=count(), num_calls=dcount(CorrelationId)
| extend avg_participants = todecimal(num_participants) / todecimal(num_calls)

範例輸出：

通話概觀查詢

每個群組通話的參與者數目

// Count number of participants per group call
ACSCallSummary
| where CallType == 'Group'
| distinct CorrelationId, ParticipantId
| summarize num_participants=count() by CorrelationId
| summarize participant_counts=count() by num_participants
| order by num_participants asc 
| render columnchart with  (xcolumn = num_participants, title="Number of participants per group call")

範例輸出：

每個群組通話的參與者數目查詢

通話類型的比率

// Ratio of call types
ACSCallSummary
| summarize call_types=dcount(CorrelationId) by CallType
| render piechart title="Call Type Ratio"

範例輸出：

通話類型的比率查詢

通話持續時間分佈

// Call duration histogram
ACSCallSummary
| distinct CorrelationId, CallDuration
|summarize duration_counts=count() by CallDuration
| order by CallDuration asc
| render columnchart with (xcolumn = CallDuration, title="Call duration histogram")

範例輸出：

通話持續時間查詢

通話持續時間百分位數

// Call duration percentiles
ACSCallSummary
| distinct CorrelationId, CallDuration
| summarize avg(CallDuration), percentiles(CallDuration, 50, 90, 99)

範例輸出：

通話持續時間百分位數查詢

端點資訊查詢

每個通話的端點數目

// Count number of calls and endpoints,
// and print average endpoints per call
ACSCallSummary
| distinct CorrelationId, EndpointId
| summarize num_endpoints=count(), num_calls=dcount(CorrelationId)
| extend avg_endpoints = todecimal(num_endpoints) / todecimal(num_calls)

範例輸出：

每個通話的端點數目查詢

SDK 版本的比率

// Ratio of SDK Versions
ACSCallSummary
| distinct CorrelationId, ParticipantId, EndpointId, SdkVersion
| summarize sdk_counts=count() by SdkVersion
| order by SdkVersion asc
| render piechart title="SDK Version Ratio"

範例輸出：

此圓形圖顯示 SDK 版本的比率。此資料表顯示 SDK 版本

OS 版本的比率 (簡化的 OS 名稱)

// Ratio of OS Versions (simplified OS name)
ACSCallSummary
| distinct CorrelationId, ParticipantId, EndpointId, OsVersion
| extend simple_os = case(  indexof(OsVersion, "Android") != -1, tostring(split(OsVersion, ";")[0]),
                            indexof(OsVersion, "Darwin") != -1, tostring(split(OsVersion, ":")[0]),
                            indexof(OsVersion, "Windows") != -1, tostring(split(OsVersion, ".")[0]),
                            OsVersion
                        )
| summarize os_counts=count() by simple_os
| order by simple_os asc
| render piechart title="OS Version Ratio"

範例輸出：

此圓形圖顯示作業系統比率此資料表顯示作業系統版本

媒體串流查詢

每個通話的串流

// Count number of calls and streams,
// and print average streams per call
ACSCallDiagnostics
| summarize num_streams=count(), num_calls=dcount(CorrelationId)
| extend avg_streams = todecimal(num_streams) / todecimal(num_calls)

範例輸出：

每個通話的串流查詢

每個通話的串流長條圖

// Distribution of streams per call
ACSCallDiagnostics
| summarize streams_per_call=count() by CorrelationId
| summarize stream_counts=count() by streams_per_call
| order by streams_per_call asc
| render columnchart title="Streams per call histogram"

每個通話的串流長條圖

媒體類型的比率

// Ratio of media types by call
ACSCallDiagnostics
| summarize media_types=count() by MediaType
| render piechart title="Media Type Ratio"

此圓形圖顯示媒體類型比率

品質計量查詢

平均遙測值

// Average telemetry values over all streams
ACSCallDiagnostics
| summarize Avg_JitterAvg=avg(JitterAvg),
            Avg_JitterMax=avg(JitterMax),
            Avg_RoundTripTimeAvg=avg(RoundTripTimeAvg),
            Avg_RoundTripTimeMax=avg(RoundTripTimeMax),
            Avg_PacketLossRateAvg=avg(PacketLossRateAvg),
            Avg_PacketLossRateMax=avg(PacketLossRateMax)

平均遙測值

JitterAvg 長條圖

// Jitter Average Histogram
ACSCallDiagnostics
| where isnotnull(JitterAvg)
| summarize JitterAvg_counts=count() by JitterAvg
| order by JitterAvg asc
| render columnchart with (xcolumn = JitterAvg, title="JitterAvg histogram")

抖動平均長條圖

JitterMax 長條圖

// Jitter Max Histogram
ACSCallDiagnostics
| where isnotnull(JitterMax)
|summarize JitterMax_counts=count() by JitterMax
| order by JitterMax asc
| render columnchart with (xcolumn = JitterMax, title="JitterMax histogram")

抖動上限長條圖

PacketLossRateAvg 長條圖

// PacketLossRate Average Histogram
ACSCallDiagnostics
| where isnotnull(PacketLossRateAvg)
|summarize PacketLossRateAvg_counts=count() by bin(PacketLossRateAvg, 0.01)
| order by PacketLossRateAvg asc
| render columnchart with (xcolumn = PacketLossRateAvg, title="PacketLossRateAvg histogram")

封包遺失平均長條圖

PacketLossRateMax 長條圖

// PacketLossRate Max Histogram
ACSCallDiagnostics
| where isnotnull(PacketLossRateMax)
|summarize PacketLossRateMax_counts=count() by bin(PacketLossRateMax, 0.01)
| order by PacketLossRateMax asc
| render columnchart with (xcolumn = PacketLossRateMax, title="PacketLossRateMax histogram")

封包遺失上限長條圖

RoundTripTimeAvg 長條圖

// RoundTripTime Average Histogram
ACSCallDiagnostics
| where isnotnull(RoundTripTimeAvg)
|summarize RoundTripTimeAvg_counts=count() by RoundTripTimeAvg
| order by RoundTripTimeAvg asc
| render columnchart with (xcolumn = RoundTripTimeAvg, title="RoundTripTimeAvg histogram")

RTT 平均長條圖

RoundTripTimeMax 長條圖

// RoundTripTime Max Histogram
ACSCallDiagnostics
| where isnotnull(RoundTripTimeMax)
|summarize RoundTripTimeMax_counts=count() by RoundTripTimeMax
| order by RoundTripTimeMax asc
| render columnchart with (xcolumn = RoundTripTimeMax, title="RoundTripTimeMax histogram")

RTT 上限長條圖

不良抖動品質

// Get proportion of calls with poor quality jitter
// (defined as jitter being higher than 30ms)
ACSCallDiagnostics
| extend JitterQuality = iff(JitterAvg > 30, "Poor", "Good")
| summarize count() by JitterQuality
| render piechart title="Jitter Quality"

抖動品質

PacketLossRate 品質

// Get proportion of calls with poor quality packet loss
// rate (defined as packet loss being higher than 10%)
ACSCallDiagnostics
| extend PacketLossRateQuality = iff(PacketLossRateAvg > 0.1, "Poor", "Good")
| summarize count() by PacketLossRateQuality
| render piechart title="Packet Loss Rate Quality"

封包遺失率品質

RoundTripTime 品質

// Get proportion of calls with poor quality packet loss
// rate (defined as packet loss being higher than 10%)
ACSCallDiagnostics
| extend PacketLossRateQuality = iff(PacketLossRateAvg > 0.1, "Poor", "Good")
| summarize count() by PacketLossRateQuality
| render piechart title="Packet Loss Rate Quality"

RTT 品質

可參數化查詢

過去一週的每日通話數

// Histogram of daily calls over the last week
ACSCallSummary
| where CallStartTime > now() - 7d
| distinct CorrelationId, CallStartTime
| extend hour  = floor(CallStartTime, 1d)
| summarize event_count=count() by day
| sort by day asc
| render columnchart title="Number of calls in last week"

過去一週的每日通話數

過去一天的每小時通話數

// Histogram of calls per hour in the last day
ACSCallSummary
| where CallStartTime > now() - 1d
| distinct CorrelationId, CallStartTime
| extend hour = floor(CallStartTime, 1h)
| summarize event_count=count() by hour
| sort by hour asc
| render columnchart title="Number of calls per hour in last day"

過去一天的每小時通話數

分享方式：

查詢通話記錄

概觀和存取

存取

通話摘要和通話診斷記錄的預設查詢套件

通話概觀查詢

每個通話的參與者數目

每個群組通話的參與者數目

通話類型的比率

通話持續時間分佈

通話持續時間百分位數

端點資訊查詢

每個通話的端點數目

SDK 版本的比率

OS 版本的比率 (簡化的 OS 名稱)

媒體串流查詢

每個通話的串流

每個通話的串流長條圖

媒體類型的比率

品質計量查詢

平均遙測值

JitterAvg 長條圖

JitterMax 長條圖

PacketLossRateAvg 長條圖

PacketLossRateMax 長條圖

RoundTripTimeAvg 長條圖

RoundTripTimeMax 長條圖

不良抖動品質

PacketLossRate 品質

RoundTripTime 品質

可參數化查詢

過去一週的每日通話數

過去一天的每小時通話數

意見反映

更多資源