Forum Discussion
Maximum allowed size of 1000000 rows
Hi,
I have to prepare the following Lag report
In above case, in January 2022,13413 number of accounts opened. In following months there is a count of A/cs which are not closed for eg As on 28 feb 22, 3 accounts were closed so the no. of accounts active are 13410. To acheive this I have 3 measures
Columns = As on Date (Date Dim Table)
How can I solve this error?
Hi PriyankaA905 ,
The reason for such error messages is that Power BI creates queries as efficiently as possible. However, in some cases, the generated queries may not be efficient enough to avoid refresh failures. One such case is when the generated query retrieves too many rows (more than 1 million rows) from the back-end data source, the following error will occur.The resultset of a query to external data source has exceeded the maximum allowed size of '1000000' rows.related document link.
Use DirectQuery in Power BI Desktop - Power BI | Microsoft Docs
If the problem is still not resolved, please provide detailed error information and let me know immediately. Looking forward to your reply.
Best Regards,
Henry
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
2 Replies
- PriyankaA905Frequent Visitor
I am attaching sample Data here:
Customer Dim:
ACNTS_INTERNAL_ACNUM ACNTS_OPENING_DATE ACNTS_CLOSURE_DATE Lag_opening date 1 1-Jan-22 Jan-22 2 1-Jan-22 Jan-22 3 3-Jan-22 Jan-22 4 3-Jan-22 Jan-22 5 3-Jan-22 18-Jan-22 Jan-22 6 3-Jan-22 2-Mar-22 Jan-22 7 3-Jan-22 7-Mar-22 Jan-22 8 3-Jan-22 16-Mar-22 Jan-22 9 3-Jan-22 13-Apr-22 Jan-22 10 4-Jan-22 Jan-22 11 4-Jan-22 Jan-22 12 4-Jan-22 15-Jan-22 Jan-22 13 4-Jan-22 8-Mar-22 Jan-22 14 4-Jan-22 12-Apr-22 Jan-22 16 5-Jan-22 Jan-22 17 6-Jan-22 Jan-22 18 6-Jan-22 Jan-22 20 7-Jan-22 Jan-22 21 8-Jan-22 Jan-22 22 8-Jan-22 Jan-22 23 10-Jan-22 Jan-22 25 10-Jan-22 11-Mar-22 Jan-22 26 11-Jan-22 Jan-22 28 12-Jan-22 Jan-22 29 12-Jan-22 Jan-22 31 12-Jan-22 28-Jan-22 Jan-22 32 12-Jan-22 16-Mar-22 Jan-22 33 12-Jan-22 27-Apr-22 Jan-22 34 13-Jan-22 Jan-22 36 14-Jan-22 Jan-22 37 14-Jan-22 Jan-22 39 15-Jan-22 Jan-22 40 16-Jan-22 Jan-22 41 16-Jan-22 Jan-22 42 17-Jan-22 Jan-22 44 18-Jan-22 Jan-22 45 18-Jan-22 Jan-22 46 18-Jan-22 24-Mar-22 Jan-22 47 19-Jan-22 Jan-22 48 19-Jan-22 Jan-22 50 20-Jan-22 Jan-22 51 21-Jan-22 Jan-22 53 21-Jan-22 7-Apr-22 Jan-22 54 22-Jan-22 Jan-22 56 24-Jan-22 Jan-22 58 24-Jan-22 2-Feb-22 Jan-22 59 25-Jan-22 Jan-22 60 25-Jan-22 Jan-22 61 25-Jan-22 2-May-22 Jan-22 62 26-Jan-22 Jan-22 63 26-Jan-22 Jan-22 64 27-Jan-22 Jan-22 65 27-Jan-22 Jan-22 66 27-Jan-22 27-Jan-22 Jan-22 67 28-Jan-22 Jan-22 68 28-Jan-22 Jan-22 69 28-Jan-22 30-Apr-22 Jan-22 70 29-Jan-22 Jan-22 71 29-Jan-22 Jan-22 72 29-Jan-22 11-Feb-22 Jan-22 73 29-Jan-22 25-Feb-22 Jan-22 74 29-Jan-22 8-Apr-22 Jan-22 75 30-Jan-22 Jan-22 76 30-Jan-22 Jan-22 77 31-Jan-22 Jan-22 78 31-Jan-22 Jan-22 80 1-Feb-22 Feb-22 81 1-Feb-22 11-Feb-22 Feb-22 82 1-Feb-22 21-Mar-22 Feb-22 83 1-Feb-22 13-Apr-22 Feb-22 84 2-Feb-22 Feb-22 85 2-Feb-22 Feb-22 86 3-Feb-22 Feb-22 87 3-Feb-22 Feb-22 89 4-Feb-22 Feb-22 90 4-Feb-22 5-Mar-22 Feb-22 91 4-Feb-22 31-Mar-22 Feb-22 92 4-Feb-22 4-May-22 Feb-22 93 5-Feb-22 Feb-22 94 5-Feb-22 Feb-22 97 6-Feb-22 Feb-22 98 7-Feb-22 Feb-22 99 7-Feb-22 Feb-22 100 7-Feb-22 7-Feb-22 Feb-22 101 8-Feb-22 Feb-22 102 8-Feb-22 Feb-22 103 8-Feb-22 2-Mar-22 Feb-22 104 8-Feb-22 3-Mar-22 Feb-22 105 9-Feb-22 Feb-22 106 9-Feb-22 Feb-22 107 10-Feb-22 Feb-22 108 10-Feb-22 Feb-22 109 11-Feb-22 Feb-22 110 11-Feb-22 Feb-22 111 11-Feb-22 21-Mar-22 Feb-22 112 12-Feb-22 Feb-22 113 12-Feb-22 Feb-22 114 14-Feb-22 Feb-22 115 14-Feb-22 Feb-22 116 15-Feb-22 Feb-22 117 15-Feb-22 Feb-22 119 15-Feb-22 30-Apr-22 Feb-22 120 16-Feb-22 Feb-22 121 16-Feb-22 Feb-22 122 16-Feb-22 25-Apr-22 Feb-22 123 17-Feb-22 Feb-22 124 17-Feb-22 Feb-22 125 17-Feb-22 12-Apr-22 Feb-22 126 18-Feb-22 Feb-22 127 18-Feb-22 Feb-22 128 18-Feb-22 30-Mar-22 Feb-22 129 19-Feb-22 Feb-22 130 19-Feb-22 Feb-22 131 20-Feb-22 Feb-22 132 20-Feb-22 Feb-22 133 21-Feb-22 Feb-22 134 21-Feb-22 Feb-22 135 22-Feb-22 Feb-22 136 22-Feb-22 Feb-22 137 23-Feb-22 Feb-22 138 23-Feb-22 Feb-22 139 24-Feb-22 Feb-22 140 24-Feb-22 Feb-22 141 24-Feb-22 18-Apr-22 Feb-22 142 24-Feb-22 4-May-22 Feb-22 143 25-Feb-22 Feb-22 144 25-Feb-22 Feb-22 145 26-Feb-22 Feb-22 146 26-Feb-22 Feb-22 147 28-Feb-22 Feb-22 148 28-Feb-22 Feb-22 149 28-Feb-22 8-Apr-22 Feb-22 150 28-Feb-22 28-Apr-22 Feb-22 151 1-Mar-22 Mar-22 152 1-Mar-22 Mar-22 153 2-Mar-22 Mar-22 154 2-Mar-22 Mar-22 155 3-Mar-22 Mar-22 156 3-Mar-22 Mar-22 157 3-Mar-22 8-Apr-22 Mar-22 158 4-Mar-22 Mar-22 159 4-Mar-22 Mar-22 160 5-Mar-22 Mar-22 161 5-Mar-22 Mar-22 162 5-Mar-22 23-Mar-22 Mar-22 163 6-Mar-22 Mar-22 164 6-Mar-22 Mar-22 165 7-Mar-22 Mar-22 166 7-Mar-22 Mar-22 167 7-Mar-22 16-Mar-22 Mar-22 168 8-Mar-22 Mar-22 169 8-Mar-22 Mar-22 170 8-Mar-22 11-Apr-22 Mar-22 171 9-Mar-22 Mar-22 172 9-Mar-22 Mar-22 173 9-Mar-22 26-Apr-22 Mar-22 174 10-Mar-22 Mar-22 175 10-Mar-22 Mar-22 176 10-Mar-22 16-Apr-22 Mar-22 177 11-Mar-22 Mar-22 178 11-Mar-22 Mar-22 179 11-Mar-22 2-Apr-22 Mar-22 180 12-Mar-22 Mar-22 181 12-Mar-22 Mar-22 182 12-Mar-22 16-Apr-22 Mar-22 183 12-Mar-22 4-May-22 Mar-22 184 13-Mar-22 Mar-22 185 14-Mar-22 Mar-22 186 14-Mar-22 Mar-22 187 14-Mar-22 16-Mar-22 Mar-22 188 15-Mar-22 Mar-22 189 15-Mar-22 Mar-22 190 16-Mar-22 Mar-22 191 16-Mar-22 Mar-22 192 17-Mar-22 Mar-22 193 17-Mar-22 Mar-22 194 17-Mar-22 13-Apr-22 Mar-22 195 18-Mar-22 Mar-22 196 18-Mar-22 Mar-22 197 19-Mar-22 Mar-22 198 19-Mar-22 Mar-22 199 21-Mar-22 Mar-22 200 21-Mar-22 Mar-22 201 22-Mar-22 Mar-22 202 22-Mar-22 Mar-22 203 22-Mar-22 22-Mar-22 Mar-22 204 23-Mar-22 Mar-22 205 23-Mar-22 Mar-22 206 23-Mar-22 23-Mar-22 Mar-22 207 23-Mar-22 28-Mar-22 Mar-22 208 23-Mar-22 5-Apr-22 Mar-22 209 24-Mar-22 Mar-22 210 24-Mar-22 Mar-22 211 24-Mar-22 21-Apr-22 Mar-22 212 25-Mar-22 Mar-22 213 25-Mar-22 Mar-22 214 26-Mar-22 Mar-22 215 26-Mar-22 Mar-22 216 26-Mar-22 4-May-22 Mar-22 217 27-Mar-22 Mar-22 218 27-Mar-22 Mar-22 219 28-Mar-22 Mar-22 220 28-Mar-22 Mar-22 221 29-Mar-22 Mar-22 222 29-Mar-22 Mar-22 223 29-Mar-22 16-Apr-22 Mar-22 224 29-Mar-22 27-Apr-22 Mar-22 225 30-Mar-22 Mar-22 226 30-Mar-22 Mar-22 227 31-Mar-22 Mar-22 228 31-Mar-22 Mar-22 Date Dim:
AS_ON_DATE 31-Jan-22 28-Feb-22 31-Mar-22 30-Apr-22 - v-henryk-mstf
Community Support
Hi PriyankaA905 ,
The reason for such error messages is that Power BI creates queries as efficiently as possible. However, in some cases, the generated queries may not be efficient enough to avoid refresh failures. One such case is when the generated query retrieves too many rows (more than 1 million rows) from the back-end data source, the following error will occur.The resultset of a query to external data source has exceeded the maximum allowed size of '1000000' rows.related document link.
Use DirectQuery in Power BI Desktop - Power BI | Microsoft Docs
If the problem is still not resolved, please provide detailed error information and let me know immediately. Looking forward to your reply.
Best Regards,
Henry
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.