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  • C# Date Time Picker to Text?

    - by user3691826
    Im trying to get a text from a file into date format for a label. What i currently have works great for a DateTimePicker however im wanting to now use a label to display the date rather than a DateTimePicker. This is what currently works when getting the value to a DateTimePicker: dateTimeMFR.Value = this.myKeyVault.MFRDate; and this is what im attempting to make work in a label: DateTimePicker myDate = new DateTimePicker(); myDate.Value = myKeyVault.MFRDate; txtMFR.Text = myDate.Text; Thanks for any help on the matter.

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  • Time display query in sql

    - by shanks
    I have following data UserID UserName LogTime LogDate 1 S 9:00 21/5/2010 1 S 10:00 21/5/2010 1 S 11:00 21/5/2010 1 S 12:00 21/5/2010 Need Output as:- 1 s 9:00 10:00 21/5/2010 1 s 11:00 12:00 21/5/2010

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  • MySQL: Order by time (MM:SS)?

    - by Shpigford
    I'm currently storing various metadata about videos and one of those bits of data is the length of a video. So if a video is 10 minutes 35 seconds long, it's saved as "10:35" in the database. But what I'd like to do is retrieve a listing of videos by length (longest first, shortest last). The problem I'm having is that if a video is "2:56", it's coming up as longest because the number 2 is more than the number 1 in. So, how can I order data based on that length field so that "10:35" is recognized as being longer than "2:56" (as per my example)?

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  • Android Convert Central Time to Local Time

    - by chedstone
    I have a MySql database that stores a timestamp for each record I insert. I pull that timestamp into my Android application as a string. My database is located on a server that has a TimeZone of CST. I want to convert that CST timestamp to the Android device's local time. Can someone help with this?

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  • Same SELECT used in an INSERT has different execution plan

    - by amacias
    A customer complained that a query and its INSERT counterpart had different execution plans, and of course, the INSERT was slower. First lets look at the SELECT : SELECT ua_tr_rundatetime,        ua_ch_treatmentcode,        ua_tr_treatmentcode,        ua_ch_cellid,        ua_tr_cellid FROM   (SELECT DISTINCT CH.treatmentcode AS UA_CH_TREATMENTCODE,                         CH.cellid        AS UA_CH_CELLID         FROM    CH,                 DL         WHERE  CH.contactdatetime > SYSDATE - 5                AND CH.treatmentcode = DL.treatmentcode) CH_CELLS,        (SELECT DISTINCT T.treatmentcode AS UA_TR_TREATMENTCODE,                         T.cellid        AS UA_TR_CELLID,                         T.rundatetime   AS UA_TR_RUNDATETIME         FROM    T,                 DL         WHERE  T.treatmentcode = DL.treatmentcode) TRT_CELLS WHERE  CH_CELLS.ua_ch_treatmentcode(+) = TRT_CELLS.ua_tr_treatmentcode;  The query has 2 DISTINCT subqueries.  The execution plan shows one with DISTICT Placement transformation applied and not the other. The view in Step 5 has the prefix VW_DTP which means DISTINCT Placement. -------------------------------------------------------------------- | Id  | Operation                    | Name            | Cost (%CPU) -------------------------------------------------------------------- |   0 | SELECT STATEMENT             |                 |   272K(100) |*  1 |  HASH JOIN OUTER             |                 |   272K  (1) |   2 |   VIEW                       |                 |  4408   (1) |   3 |    HASH UNIQUE               |                 |  4408   (1) |*  4 |     HASH JOIN                |                 |  4407   (1) |   5 |      VIEW                    | VW_DTP_48BAF62C |  1660   (2) |   6 |       HASH UNIQUE            |                 |  1660   (2) |   7 |        TABLE ACCESS FULL     | DL              |  1644   (1) |   8 |      TABLE ACCESS FULL       | T               |  2744   (1) |   9 |   VIEW                       |                 |   267K  (1) |  10 |    HASH UNIQUE               |                 |   267K  (1) |* 11 |     HASH JOIN                |                 |   267K  (1) |  12 |      PARTITION RANGE ITERATOR|                 |   266K  (1) |* 13 |       TABLE ACCESS FULL      | CH              |   266K  (1) |  14 |      TABLE ACCESS FULL       | DL              |  1644   (1) -------------------------------------------------------------------- Query Block Name / Object Alias (identified by operation id): -------------------------------------------------------------    1 - SEL$1    2 - SEL$AF418D5F / TRT_CELLS@SEL$1    3 - SEL$AF418D5F    5 - SEL$F6AECEDE / VW_DTP_48BAF62C@SEL$48BAF62C    6 - SEL$F6AECEDE    7 - SEL$F6AECEDE / DL@SEL$3    8 - SEL$AF418D5F / T@SEL$3    9 - SEL$2        / CH_CELLS@SEL$1   10 - SEL$2   13 - SEL$2        / CH@SEL$2   14 - SEL$2        / DL@SEL$2 Predicate Information (identified by operation id): ---------------------------------------------------    1 - access("CH_CELLS"."UA_CH_TREATMENTCODE"="TRT_CELLS"."UA_TR_TREATMENTCODE")    4 - access("T"."TREATMENTCODE"="ITEM_1")   11 - access("CH"."TREATMENTCODE"="DL"."TREATMENTCODE")   13 - filter("CH"."CONTACTDATETIME">SYSDATE@!-5) The outline shows PLACE_DISTINCT(@"SEL$3" "DL"@"SEL$3") indicating that the QB3 is the one that got the transformation. Outline Data -------------   /*+       BEGIN_OUTLINE_DATA       IGNORE_OPTIM_EMBEDDED_HINTS       OPTIMIZER_FEATURES_ENABLE('11.2.0.3')       DB_VERSION('11.2.0.3')       ALL_ROWS       OUTLINE_LEAF(@"SEL$2")       OUTLINE_LEAF(@"SEL$F6AECEDE")       OUTLINE_LEAF(@"SEL$AF418D5F") PLACE_DISTINCT(@"SEL$3" "DL"@"SEL$3")       OUTLINE_LEAF(@"SEL$1")       OUTLINE(@"SEL$48BAF62C")       OUTLINE(@"SEL$3")       NO_ACCESS(@"SEL$1" "TRT_CELLS"@"SEL$1")       NO_ACCESS(@"SEL$1" "CH_CELLS"@"SEL$1")       LEADING(@"SEL$1" "TRT_CELLS"@"SEL$1" "CH_CELLS"@"SEL$1")       USE_HASH(@"SEL$1" "CH_CELLS"@"SEL$1")       FULL(@"SEL$2" "CH"@"SEL$2")       FULL(@"SEL$2" "DL"@"SEL$2")       LEADING(@"SEL$2" "CH"@"SEL$2" "DL"@"SEL$2")       USE_HASH(@"SEL$2" "DL"@"SEL$2")       USE_HASH_AGGREGATION(@"SEL$2")       NO_ACCESS(@"SEL$AF418D5F" "VW_DTP_48BAF62C"@"SEL$48BAF62C")       FULL(@"SEL$AF418D5F" "T"@"SEL$3")       LEADING(@"SEL$AF418D5F" "VW_DTP_48BAF62C"@"SEL$48BAF62C" "T"@"SEL$3")       USE_HASH(@"SEL$AF418D5F" "T"@"SEL$3")       USE_HASH_AGGREGATION(@"SEL$AF418D5F")       FULL(@"SEL$F6AECEDE" "DL"@"SEL$3")       USE_HASH_AGGREGATION(@"SEL$F6AECEDE")       END_OUTLINE_DATA   */ The 10053 shows there is a comparative of cost with and without the transformation. This means the transformation belongs to Cost-Based Query Transformations (CBQT). In SEL$3 the optimization of the query block without the transformation is 6659.73 and with the transformation is 4408.41 so the transformation is kept. GBP/DP: Checking validity of GBP/DP for query block SEL$3 (#3) DP: Checking validity of distinct placement for query block SEL$3 (#3) DP: Using search type: linear DP: Considering distinct placement on query block SEL$3 (#3) DP: Starting iteration 1, state space = (5) : (0) DP: Original query DP: Costing query block. DP: Updated best state, Cost = 6659.73 DP: Starting iteration 2, state space = (5) : (1) DP: Using DP transformation in this iteration. DP: Transformed query DP: Costing query block. DP: Updated best state, Cost = 4408.41 DP: Doing DP on the original QB. DP: Doing DP on the preserved QB. In SEL$2 the cost without the transformation is less than with it so it is not kept. GBP/DP: Checking validity of GBP/DP for query block SEL$2 (#2) DP: Checking validity of distinct placement for query block SEL$2 (#2) DP: Using search type: linear DP: Considering distinct placement on query block SEL$2 (#2) DP: Starting iteration 1, state space = (3) : (0) DP: Original query DP: Costing query block. DP: Updated best state, Cost = 267936.93 DP: Starting iteration 2, state space = (3) : (1) DP: Using DP transformation in this iteration. DP: Transformed query DP: Costing query block. DP: Not update best state, Cost = 267951.66 To the same query an INSERT INTO is added and the result is a very different execution plan. INSERT  INTO cc               (ua_tr_rundatetime,                ua_ch_treatmentcode,                ua_tr_treatmentcode,                ua_ch_cellid,                ua_tr_cellid)SELECT ua_tr_rundatetime,       ua_ch_treatmentcode,       ua_tr_treatmentcode,       ua_ch_cellid,       ua_tr_cellidFROM   (SELECT DISTINCT CH.treatmentcode AS UA_CH_TREATMENTCODE,                        CH.cellid        AS UA_CH_CELLID        FROM    CH,                DL        WHERE  CH.contactdatetime > SYSDATE - 5               AND CH.treatmentcode = DL.treatmentcode) CH_CELLS,       (SELECT DISTINCT T.treatmentcode AS UA_TR_TREATMENTCODE,                        T.cellid        AS UA_TR_CELLID,                        T.rundatetime   AS UA_TR_RUNDATETIME        FROM    T,                DL        WHERE  T.treatmentcode = DL.treatmentcode) TRT_CELLSWHERE  CH_CELLS.ua_ch_treatmentcode(+) = TRT_CELLS.ua_tr_treatmentcode;----------------------------------------------------------| Id  | Operation                     | Name | Cost (%CPU)----------------------------------------------------------|   0 | INSERT STATEMENT              |      |   274K(100)|   1 |  LOAD TABLE CONVENTIONAL      |      |            |*  2 |   HASH JOIN OUTER             |      |   274K  (1)|   3 |    VIEW                       |      |  6660   (1)|   4 |     SORT UNIQUE               |      |  6660   (1)|*  5 |      HASH JOIN                |      |  6659   (1)|   6 |       TABLE ACCESS FULL       | DL   |  1644   (1)|   7 |       TABLE ACCESS FULL       | T    |  2744   (1)|   8 |    VIEW                       |      |   267K  (1)|   9 |     SORT UNIQUE               |      |   267K  (1)|* 10 |      HASH JOIN                |      |   267K  (1)|  11 |       PARTITION RANGE ITERATOR|      |   266K  (1)|* 12 |        TABLE ACCESS FULL      | CH   |   266K  (1)|  13 |       TABLE ACCESS FULL       | DL   |  1644   (1)----------------------------------------------------------Query Block Name / Object Alias (identified by operation id):-------------------------------------------------------------   1 - SEL$1   3 - SEL$3 / TRT_CELLS@SEL$1   4 - SEL$3   6 - SEL$3 / DL@SEL$3   7 - SEL$3 / T@SEL$3   8 - SEL$2 / CH_CELLS@SEL$1   9 - SEL$2  12 - SEL$2 / CH@SEL$2  13 - SEL$2 / DL@SEL$2Predicate Information (identified by operation id):---------------------------------------------------   2 - access("CH_CELLS"."UA_CH_TREATMENTCODE"="TRT_CELLS"."UA_TR_TREATMENTCODE")   5 - access("T"."TREATMENTCODE"="DL"."TREATMENTCODE")  10 - access("CH"."TREATMENTCODE"="DL"."TREATMENTCODE")  12 - filter("CH"."CONTACTDATETIME">SYSDATE@!-5)Outline Data-------------  /*+      BEGIN_OUTLINE_DATA      IGNORE_OPTIM_EMBEDDED_HINTS      OPTIMIZER_FEATURES_ENABLE('11.2.0.3')      DB_VERSION('11.2.0.3')      ALL_ROWS      OUTLINE_LEAF(@"SEL$2")      OUTLINE_LEAF(@"SEL$3")      OUTLINE_LEAF(@"SEL$1")      OUTLINE_LEAF(@"INS$1")      FULL(@"INS$1" "CC"@"INS$1")      NO_ACCESS(@"SEL$1" "TRT_CELLS"@"SEL$1")      NO_ACCESS(@"SEL$1" "CH_CELLS"@"SEL$1")      LEADING(@"SEL$1" "TRT_CELLS"@"SEL$1" "CH_CELLS"@"SEL$1")      USE_HASH(@"SEL$1" "CH_CELLS"@"SEL$1")      FULL(@"SEL$2" "CH"@"SEL$2")      FULL(@"SEL$2" "DL"@"SEL$2")      LEADING(@"SEL$2" "CH"@"SEL$2" "DL"@"SEL$2")      USE_HASH(@"SEL$2" "DL"@"SEL$2")      USE_HASH_AGGREGATION(@"SEL$2")      FULL(@"SEL$3" "DL"@"SEL$3")      FULL(@"SEL$3" "T"@"SEL$3")      LEADING(@"SEL$3" "DL"@"SEL$3" "T"@"SEL$3")      USE_HASH(@"SEL$3" "T"@"SEL$3")      USE_HASH_AGGREGATION(@"SEL$3")      END_OUTLINE_DATA  */ There is no DISTINCT Placement view and no hint.The 10053 trace shows a new legend "DP: Bypassed: Not SELECT"implying that this is a transformation that it is possible only for SELECTs. GBP/DP: Checking validity of GBP/DP for query block SEL$3 (#4) DP: Checking validity of distinct placement for query block SEL$3 (#4) DP: Bypassed: Not SELECT. GBP/DP: Checking validity of GBP/DP for query block SEL$2 (#3) DP: Checking validity of distinct placement for query block SEL$2 (#3) DP: Bypassed: Not SELECT. In 12.1 (and hopefully in 11.2.0.4 when released) the restriction on applying CBQT to some DMLs and DDLs (like CTAS) is lifted.This is documented in BugTag Note:10013899.8 Allow CBQT for some DML / DDLAnd interestingly enough, it is possible to have a one-off patch in 11.2.0.3. SQL> select DESCRIPTION,OPTIMIZER_FEATURE_ENABLE,IS_DEFAULT     2  from v$system_fix_control where BUGNO='10013899'; DESCRIPTION ---------------------------------------------------------------- OPTIMIZER_FEATURE_ENABLE  IS_DEFAULT ------------------------- ---------- enable some transformations for DDL and DML statements 11.2.0.4                           1

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  • Excel Question: I need a date and time formula to convert between time zones

    - by Harold Nottingham
    Hello, I am trying to find a way to calculate a duration in days between my, time zone (Central), and (Pacific; Mountain; Eastern). Just do not know where to start. My criteria would be as follows: Cell C5:C100 would be the timestamps in this format:3/18/2010 23:45 but for different dates and times. Cell D5:D100 would be the corresponding timezone in text form: Pacific; Mountain; Eastern; Central. Cell F5 would be where the duration in days would need to be. Just not sure how to write the formula to give me what I am looking for. I appreciate any assistance in advance. Thanks

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  • Exel Question: I need a date and time formula to convert between time zones

    - by Harold Nottingham
    Hello, I am trying to find a way to calculate a duration in days between my, time zone (Central), and (Pacific; Mountain; Eastern). Just do not know where to start. My criteria would be as follows: Cell C5:C100 would be the timestamps in this format:3/18/2010 23:45 but for different dates and times. Cell D5:D100 would be the corresponding timezone in text form: Pacific; Mountain; Eastern; Central. Cell F5 would be where the duration in days would need to be. Just not sure how to write the formula to give me what I am looking for. I appreciate any assistance in advance. Thanks

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  • Taming Hopping Windows

    - by Roman Schindlauer
    At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

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  • Taming Hopping Windows

    - by Roman Schindlauer
    At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

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  • SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Signal Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Signal Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Signal Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the Signalwait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the Signal wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the Signal wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Single Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Single Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Single Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Single Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the single wait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the single wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the single wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Developing web application with time zones support

    - by outcoldman
    When you develop web application you should know that client PCs can be located anywhere on earth. Even if you develop app just for your country users you should remember it (in Russia now we have 9 time zones, before 28 of March we had 11 time zones). On big sites with many members do it very easy – you can place field “time zone” in member profile, in Sharepoint I saw this solution, and many enterprise app do it like this. But if we have simple website with blog publications or website with news and we don’t have member profiles on server, how we can support user’s time zones? I thought about this question because I wanted to develop time zone support on my own site. My case is ASP.NET MVC app and MS SQL Server DB. First, I started from learning which params we have at HTTP headers, but it doesn’t have information about it. So we can’t use regional settings and methods DateTime.ToLocalTime and DateTime.ToUniversalTime until we get user time zone on server. If we used our app before without time zones support we need to change dates from local time zone to UTC time zone (something like Greenwich Mean Time). Read more...(Redirect to http://outcoldman.ru)

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  • Opening Time-Machine OSX backup files on Windows 7?

    - by user39279
    Hi, Have Time Machine backups on a Western Digital External HD. The Time Machine backups were done on my now dead Mac G4 running OSX Leopard- I am waiting on a new iMac but in the meantime I need to access some of my backup files urgently. I have a laptop running Windows 7 so is there any safe way of accessing some of the files from the Time Machine backup on my laptop and still be able to do a full restore when the iMac arrives? Thanks -

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  • How do I restore a non-system hard drive using Time Machine under OSX?

    - by richardtallent
    I dropped one of the external drives on my Mac Pro and it started making noises... so I bought a replacement drive. No biggie, that's why I have Time Machine, right? So now that I have the new drive up and initialized, how do I actually restore the drive from backup? Time Machine is intuitive when it comes to restoring the system drive or restoring individual folders/files on the same literal device, but I'm a bit stuck in how to properly restore an entire drive that is not the boot drive. I saw one suggestion to use the same volume name as the old drive and then go into Time Machine. Haven't tried that since the information is unconfirmed. For now, I just went to the Time Machine volume, found the latest backup folder for that volume, and I'm copying the files via Finder. Of couse, I expect this to work just fine, but I feel like I'm missing something if that's the "proper" way to do this.

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  • SQL SERVER – Select Columns from Stored Procedure Resultset

    - by Pinal Dave
    It is fun to go back to basics often. Here is the one classic question: “How to select columns from Stored Procedure Resultset?” Though Stored Procedure has been introduced many years ago, the question about retrieving columns from Stored Procedure is still very popular with beginners. Let us see the solution in quick steps. First we will create a sample stored procedure. CREATE PROCEDURE SampleSP AS SELECT 1 AS Col1, 2 AS Col2 UNION SELECT 11, 22 GO Now we will create a table where we will temporarily store the result set of stored procedures. We will be using INSERT INTO and EXEC command to retrieve the values and insert into temporary table. CREATE TABLE #TempTable (Col1 INT, Col2 INT) GO INSERT INTO #TempTable EXEC SampleSP GO Next we will retrieve our data from stored procedure. SELECT * FROM #TempTable GO Finally we will clean up all the objects which we have created. DROP TABLE #TempTable DROP PROCEDURE SampleSP GO Let me know if you want me to share such back to basic tips. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Stored Procedure, SQL Tips and Tricks, T SQL

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  • How can I set the date format to my country setting?

    - by Jamina Meissner
    I am German, but I use only English software. Hence, I am also using English Ubuntu. It's not because I don't know how to install German Ubuntu. It's because I prefer to work with English software environment. However, I would like to keep date & time format in German format, just as I use a German keyboard layout in English Ubuntu. I can set the time format to 24h time. But how can I set the date format to German time format? It is irritating for me to have the day number before the time numbers: In other words, instead of "Oct 14 15:16" I want it to display "14 Okt" or (if only English language is available) "14 Oct 15:16" or "14th Oct 15:16". At least, the number of the day should be displayed before the month. In Windows, it was no problem to choose time/date/currency settings according to a chosen country. Where can I do this in Ubuntu? The best would be if I could freely enter the date/time format myself with variables (DD.MM hh.mm.ss etc). I found answers for Ubuntu 11.04, but not for Ubuntu 12.04. I am using Ubuntu 12.04, 64-bit. Keep in mind that I am a beginner. So I'd like to be able to do this via GUI, if possible. EDIT: I found the answer in a forum. Go to System Settings... and choose Language Support. There are two tabs, Language and Reginal Formats. You are by default on the Language tab. On the Language tab, click Install / Remove Languages. A window with a list of languages opens. Mark the language(s) you want to add for your time/date/currency format. Click Apply Changes. Ubuntu will now download and install the additional language files, as well as help files of other applications in this language. So don't be irritated. When Ubuntu has finished applying the changes, switch to Regional Formats tab. (Do not change the Language for menus and windows on the Language tab if you only want to change the date/time/unit format). There you can choose from the dropdown list the language for your preferred format for date/time/currency/unit. Log out and log in again to have the changes take effect.

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  • A fix for the design time error in MVVM Light V4.1

    - by Laurent Bugnion
    For those of you who installed V4.1 of MVVM Light and created a project for Windows Phone 8, you will have noticed an error showing up in the design surface (either in Visual Studio designer, or in Expression Blend). The error says: “Could not load type ‘System.ComponentModel.INotifyPropertyChanging’ from assembly ‘mscorlib.extensions’” with additional information about version numbers. The error is caused by an incompatibility between versions of System.Windows.Interactivity. Because this assembly is strongly named, any version incompatibility is causing the kind of error shown here (for an interesting discussion on the strong naming issue, see this thread on Codeplex). I managed to resolve the issue for Windows Phone 8 and will publish a cleaned up installer next week. In the mean time, in order to allow you to continue development, please follow the steps: Download the new DLLs zip package (MVVMLight_V4_1_25_WP8). Right click on the Zip file and select Properties from the context menu. Press the “Unblock” button (if available) and then OK. Right click again on the zip package and select “Extract all…”. Select a known location for the new DLLs. Open the MVVM Light project with the design time error in Visual Studio 2012. Open the References folder in the Solution Explorer. Select the following DLLs: GalaSoft.MvvmLight.dll, GalaSoft.MvvmLight.Extras.dll, Microsoft.Practices.ServiceLocation.dll and System.Windows.Interactivity.dll. Press “delete” and confirm to remove the DLLs from your project. Right click on References and select Add Reference from the context menu. Browse to the folder with the new DLLs. Select the four new DLLs and press OK. Rebuild your application, and open it again in Blend or in the Visual Studio designer. The error should be gone now. In the next few days, as time allows, I will publish a new MSI containing a fixed version of the DLLs as well as a few other improvements. This quick fix should however allow you to continue working on your Windows Phone 8 projects in design mode too.   Laurent Bugnion (GalaSoft) Subscribe | Twitter | Facebook | Flickr | LinkedIn

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  • T-SQL select where and group by date

    - by bconlon
    T-SQL has never been my favorite language, but I need to use it on a fairly regular basis and every time I seem to Google the same things. So if I add it here, it might help others with the same issues, but it will also save me time later as I will know where to look for the answers!! 1. How do I SELECT FROM WHERE to filter on a DateTime column? As it happens this is easy but I always forget. You just put the DATE value in single quotes and in standard format: SELECT StartDate FROM Customer WHERE StartDate >= '2011-01-01' ORDER BY StartDate 2. How do I then GROUP BY and get a count by StartDate? Bit trickier, but you can use the built in DATEADD and DATEDIFF to set the TIME part to midnight, allowing the GROUP BY to have a consistent value to work on: SELECT DATEADD (d, DATEDIFF(d, 0, StartDate),0) [Customer Creation Date], COUNT(*) [Number Of New Customers] FROM Customer WHERE StartDate >= '2011-01-01' GROUP BY DATEADD(d, DATEDIFF(d, 0, StartDate),0) ORDER BY [Customer Creation Date] Note: [Customer Creation Date] and [Number Of New Customers] column alias just provide more readable column headers. 3. Finally, how can you format the DATETIME to only show the DATE part (after all the TIME part is now always midnight)? The built in CONVERT function allows you to convert the DATETIME to a CHAR array using a specific format. The format is a bit arbitrary and needs looking up, but 101 is the U.S. standard mm/dd/yyyy, and 103 is the U.K. standard dd/mm/yyyy. SELECT CONVERT(CHAR(10), DATEADD(d, DATEDIFF(d, 0, StartDate),0), 103) [Customer Creation Date], COUNT(*) [Number Of New Customers] FROM Customer WHERE StartDate >= '2011-01-01' GROUP BY DATEADD(d, DATEDIFF(d, 0, StartDate),0) ORDER BY [Customer Creation Date]  #

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  • Most common parts of a SELECT SQL query?

    - by jnrbsn
    I'm writing a function that generates a SELECT SQL query. (I'm not looking for a tool that already does this.) My function currently takes the following arguments which correspond to different parts of the SELECT query (the base table name is already known): where order fields joins group limit All of these arguments will be optional so that the function generates something like this by default: SELECT * FROM `table_name` I want to order the arguments so that the most often used parts of a SELECT query are first. That way the average call to the function will use as few of the arguments as possible rather than passing a null value or something like that to skip an argument. For example, if someone wanted to use the 1st and 3rd arguments but not the rest, they might have to pass a null value as the 2nd argument in order to skip it. So, for general purpose use, how should I order the arguments? Edit: To be more precise, out of the query parts I listed above, what is the order from most used to least used? Also, I'm not looking for solutions that allow me to not have to specify the order. Edit #2: The "fields" argument will default to "*" (i.e all fields/columns).

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  • after BIOS splash, will not boot -- asks me to select an OS, but it just reboots

    - by user92040
    I'm running Linux Mint 13 MATE 64-bit. Everything has been working for several weeks. Yesterday, when I tried to boot up my computer, after the BIOS screen flashes I reach a screen with a black background that reads at the top: GNU GRUB version1.99-21ubuntu3.4 Then there is a box in which I can select from the following lines: Linux Mint 13 MATE 64-bit, 3.2.0-31-generic (/dev/sdb2) Linux Mint 13 MATE 64-bit, 3.2.0-31-generic (/dev/sdb2) -- recovery mode Previous Linux versions Memory test (memtest86+) Memory test (memtest86+, serial console 115200) At the bottom it reads: Use the ? and ? keys to select which entry is highlighed. Press enter to boot the selected OS, 'e' to edit the commands before booting or 'c' for a command-line. I have no idea why it started doing this and, worse, I have no idea how to get out of here. No matter which option I select, I can't get it to boot the OS. If I select either of the first two, it reboots to splash the BIOS and then I'm right back where I started. If I choose "Previous Linux versions" I get essentially the same screen with only two choices (which are the same as the first two choices listed above, Linux 13 MATE and the recovery mode). Again, choosing either one of those results in a reboot. If I try to run either of the memtest options, it reads: error: unknown command 'linux16', Press any key to continue... Then it brings me back to the same screen Can anyone help me please? Intel Core i5-2500 ASUS P8Z68-V LX Intel Motherboard G. Skill Ripjaws series F3-12800CL9D-8GBRL (4GB x2) Plextor 128GB M5S Series SSD

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  • Logic - Time measurement

    - by user73384
    To measure the following for tasks- Last execution time and maximum execution time for each task. CPU load/time consumed by each task over a defined period informed by application at run time. Maximum CPU load consumed by each task. Tasks have following characteristics- First task runs as background – Event information for entering only Second task - periodic – Event information for entering and exiting from task Third task is interrupt , can start any time – no information available from this task Forth task highest priority interrupt , can start any time – Event information for entering and exiting from task Should use least possible execution time and memory. 32bit increment timer available for time counting. Lets prepare and discuss the logic, It’s OK to have limitations …! Questions on understanding problem statement are welcome

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