# Scrolling performance

**URL:** https://discuss.elastic.co/t/scrolling-performance/14560
**Category:** Elasticsearch
**Created:** [November 23, 2013, 5:34pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560 "2013-11-23T17:34:06Z")
**Posts on this page:** 20
**Page:** 1

<div class="post-metadata">

### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [November 23, 2013, 5:34pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/1 "2013-11-23T17:34:06Z")

</div>

I've been trying to dump an index for further reindexing with different  
sharding settings, but found out that it's almost impossible with large  
dataset (50m, 7gb in my case).

I scroll index with packs of 5000 items per iteration and scrolling takes  
longer and longer. Like this:

first request: 5000  
fetched: 10000 , time ms: 150  
fetched: 15000 , time ms: 154  
fetched: 20000 , time ms: 134  
fetched: 25000 , time ms: 145  
fetched: 30000 , time ms: 146  
fetched: 35000 , time ms: 177  
fetched: 40000 , time ms: 223  
fetched: 45000 , time ms: 199  
fetched: 50000 , time ms: 204  
fetched: 55000 , time ms: 216  
fetched: 60000 , time ms: 223  
fetched: 65000 , time ms: 229  
fetched: 70000 , time ms: 189  
fetched: 75000 , time ms: 242  
fetched: 80000 , time ms: 198  
fetched: 85000 , time ms: 264  
fetched: 90000 , time ms: 260  
fetched: 95000 , time ms: 217  
fetched: 100000 , time ms: 285  
fetched: 105000 , time ms: 289  
fetched: 110000 , time ms: 334  
fetched: 115000 , time ms: 299  
fetched: 120000 , time ms: 311  
fetched: 125000 , time ms: 253  
fetched: 130000 , time ms: 345  
fetched: 135000 , time ms: 337  
fetched: 140000 , time ms: 345  
fetched: 145000 , time ms: 352  
fetched: 150000 , time ms: 371  
fetched: 155000 , time ms: 416  
fetched: 160000 , time ms: 398  
fetched: 165000 , time ms: 452  
fetched: 170000 , time ms: 405  
fetched: 175000 , time ms: 404  
fetched: 180000 , time ms: 421  
fetched: 185000 , time ms: 426  
fetched: 190000 , time ms: 474  
fetched: 195000 , time ms: 446  
fetched: 200000 , time ms: 360  
fetched: 205000 , time ms: 457  
fetched: 210000 , time ms: 470  
fetched: 215000 , time ms: 477  
fetched: 220000 , time ms: 522  
fetched: 225000 , time ms: 397  
fetched: 230000 , time ms: 508  
fetched: 235000 , time ms: 532  
fetched: 240000 , time ms: 523  
fetched: 245000 , time ms: 567  
fetched: 250000 , time ms: 570  
fetched: 255000 , time ms: 552  
fetched: 260000 , time ms: 562  
fetched: 265000 , time ms: 593  
fetched: 270000 , time ms: 610  
fetched: 275000 , time ms: 585  
fetched: 280000 , time ms: 529  
fetched: 285000 , time ms: 604  
fetched: 290000 , time ms: 614  
fetched: 295000 , time ms: 663  
fetched: 300000 , time ms: 634  
fetched: 305000 , time ms: 646  
fetched: 310000 , time ms: 689  
fetched: 315000 , time ms: 580  
fetched: 320000 , time ms: 674  
fetched: 325000 , time ms: 682  
fetched: 330000 , time ms: 694  
fetched: 335000 , time ms: 734  
fetched: 340000 , time ms: 717  
fetched: 345000 , time ms: 725  
fetched: 350000 , time ms: 726  
fetched: 355000 , time ms: 700  
fetched: 360000 , time ms: 701  
fetched: 365000 , time ms: 610  
fetched: 370000 , time ms: 767  
fetched: 375000 , time ms: 810  
fetched: 380000 , time ms: 784  
fetched: 385000 , time ms: 801  
fetched: 390000 , time ms: 851  
fetched: 395000 , time ms: 805  
fetched: 400000 , time ms: 655  
fetched: 405000 , time ms: 869  
fetched: 410000 , time ms: 838  
fetched: 415000 , time ms: 1119  
fetched: 420000 , time ms: 1167  
fetched: 425000 , time ms: 1770  
fetched: 430000 , time ms: 1727  
fetched: 435000 , time ms: 885  
fetched: 440000 , time ms: 898  
fetched: 445000 , time ms: 905  
fetched: 450000 , time ms: 731  
fetched: 455000 , time ms: 795  
fetched: 460000 , time ms: 956  
fetched: 465000 , time ms: 918  
fetched: 470000 , time ms: 905  
fetched: 475000 , time ms: 972  
fetched: 480000 , time ms: 988  
fetched: 485000 , time ms: 887  
fetched: 490000 , time ms: 991  
fetched: 495000 , time ms: 1047  
fetched: 500000 , time ms: 812  
fetched: 505000 , time ms: 1066  
fetched: 510000 , time ms: 1091  
fetched: 515000 , time ms: 1046  
fetched: 520000 , time ms: 1042  
fetched: 525000 , time ms: 1247  
fetched: 530000 , time ms: 1060  
fetched: 535000 , time ms: 1048  
fetched: 540000 , time ms: 1099  
fetched: 545000 , time ms: 1093  
fetched: 550000 , time ms: 1157  
fetched: 555000 , time ms: 1114  
fetched: 560000 , time ms: 1085  
fetched: 565000 , time ms: 1129  
fetched: 570000 , time ms: 1193  
fetched: 575000 , time ms: 1149  
fetched: 580000 , time ms: 1175  
fetched: 585000 , time ms: 1262  
fetched: 590000 , time ms: 1180  
fetched: 595000 , time ms: 1228  
fetched: 600000 , time ms: 1199  
fetched: 605000 , time ms: 1314  
fetched: 610000 , time ms: 1179  
fetched: 615000 , time ms: 1290  
fetched: 620000 , time ms: 994  
fetched: 625000 , time ms: 1259  
fetched: 630000 , time ms: 1417  
fetched: 635000 , time ms: 1282  
fetched: 640000 , time ms: 1383  
fetched: 645000 , time ms: 1297  
fetched: 650000 , time ms: 1441  
fetched: 655000 , time ms: 1452  
fetched: 660000 , time ms: 1398  
fetched: 665000 , time ms: 1550  
fetched: 670000 , time ms: 1642  
fetched: 675000 , time ms: 1489  
fetched: 680000 , time ms: 1361  
fetched: 685000 , time ms: 1495  
fetched: 690000 , time ms: 1376  
fetched: 695000 , time ms: 1230  
fetched: 700000 , time ms: 1492  
fetched: 705000 , time ms: 1509  
fetched: 710000 , time ms: 1425  
fetched: 715000 , time ms: 1549  
fetched: 720000 , time ms: 1572  
fetched: 725000 , time ms: 1526  
fetched: 730000 , time ms: 1587  
fetched: 735000 , time ms: 1484  
fetched: 740000 , time ms: 1652  
fetched: 745000 , time ms: 1508  
fetched: 750000 , time ms: 1630  
fetched: 755000 , time ms: 1242  
fetched: 760000 , time ms: 1621  
fetched: 765000 , time ms: 1619  
fetched: 770000 , time ms: 1542  
fetched: 775000 , time ms: 1727  
fetched: 780000 , time ms: 1252  
fetched: 785000 , time ms: 1498  
fetched: 790000 , time ms: 1766  
fetched: 795000 , time ms: 1692  
fetched: 800000 , time ms: 1589  
fetched: 805000 , time ms: 1382  
fetched: 810000 , time ms: 1404  
fetched: 815000 , time ms: 1633  
fetched: 820000 , time ms: 1788  
fetched: 825000 , time ms: 1734  
fetched: 830000 , time ms: 1799  
fetched: 835000 , time ms: 1696  
fetched: 840000 , time ms: 1763  
fetched: 845000 , time ms: 1697  
fetched: 850000 , time ms: 1915  
fetched: 855000 , time ms: 1709  
fetched: 860000 , time ms: 1531  
fetched: 865000 , time ms: 1811  
fetched: 870000 , time ms: 1849  
fetched: 875000 , time ms: 2028  
fetched: 880000 , time ms: 1858  
fetched: 885000 , time ms: 1780  
fetched: 890000 , time ms: 1762  
fetched: 895000 , time ms: 1586  
fetched: 900000 , time ms: 1803  
fetched: 905000 , time ms: 1791  
fetched: 910000 , time ms: 1821  
fetched: 915000 , time ms: 1624  
fetched: 920000 , time ms: 1709  
fetched: 925000 , time ms: 1765  
fetched: 930000 , time ms: 1892  
fetched: 935000 , time ms: 3646  
fetched: 940000 , time ms: 2576  
fetched: 945000 , time ms: 2070  
fetched: 950000 , time ms: 2401  
fetched: 955000 , time ms: 1998  
fetched: 960000 , time ms: 1924  
fetched: 965000 , time ms: 2113  
fetched: 970000 , time ms: 2037  
fetched: 975000 , time ms: 1804  
fetched: 980000 , time ms: 2143  
fetched: 985000 , time ms: 1776  
fetched: 990000 , time ms: 2092  
fetched: 995000 , time ms: 2232  
fetched: 1000000 , time ms: 1986

With packs of 20000 items:

fetched: 40000, time ms:275  
fetched: 60000, time ms:296  
fetched: 80000, time ms:297  
fetched: 100000, time ms:358  
fetched: 120000, time ms:386  
fetched: 140000, time ms:413  
fetched: 160000, time ms:443  
fetched: 180000, time ms:420  
fetched: 200000, time ms:548  
fetched: 220000, time ms:487  
fetched: 240000, time ms:557  
fetched: 260000, time ms:609  
fetched: 280000, time ms:686  
fetched: 300000, time ms:655  
fetched: 320000, time ms:697  
fetched: 340000, time ms:717  
fetched: 360000, time ms:675  
fetched: 380000, time ms:787  
fetched: 400000, time ms:808  
fetched: 420000, time ms:916  
fetched: 440000, time ms:878  
fetched: 460000, time ms:940  
fetched: 480000, time ms:1035  
fetched: 500000, time ms:975  
fetched: 520000, time ms:1000  
fetched: 540000, time ms:1116  
fetched: 560000, time ms:1074  
fetched: 580000, time ms:990  
fetched: 600000, time ms:1151  
fetched: 620000, time ms:1178  
fetched: 640000, time ms:1232  
fetched: 660000, time ms:1255  
fetched: 680000, time ms:1275  
fetched: 700000, time ms:1419  
fetched: 720000, time ms:1396  
fetched: 740000, time ms:1528  
fetched: 760000, time ms:1424  
fetched: 780000, time ms:1449  
fetched: 800000, time ms:1486  
fetched: 820000, time ms:1346  
fetched: 840000, time ms:1677  
fetched: 860000, time ms:1574  
fetched: 880000, time ms:1447  
fetched: 900000, time ms:1464  
fetched: 920000, time ms:1641  
fetched: 940000, time ms:1537  
fetched: 960000, time ms:1920  
fetched: 980000, time ms:1763  
fetched: 1000000, time ms:1900

After restart scrolling is fast at the beginning again. I am using  
elasticsearch 0.90.5.

Is this an expected behaviour or known bug?

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### Author: ![James\_Richardson](https://avatars.discourse-cdn.com/v4/letter/j/838e76/32.png) [@James\_Richardson](https://discuss.elastic.co/u/James_Richardson)
#### Post date: [November 25, 2013, 10:56pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/2 "2013-11-25T22:56:31Z")

</div>

I consider ES to be an index over some some data, rather than the data itself  
Why not just re index the source? I do this for over 1m docs for every deployment, it is very fast. Takes Takes about 20mins on a single node, using couch river.

James

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### Author: ![James\_Richardson](https://avatars.discourse-cdn.com/v4/letter/j/838e76/32.png) [@James\_Richardson](https://discuss.elastic.co/u/James_Richardson)
#### Post date: [November 25, 2013, 10:59pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/3 "2013-11-25T22:59:22Z")

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These 1m items give an index size of about 4gb, for comparison.

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### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [November 26, 2013, 5:59am UTC](https://discuss.elastic.co/t/scrolling-performance/14560/4 "2013-11-26T05:59:00Z")

</div>

20 minutes isn't fast, it's not very fast for sure, you know. We  
deploy up to 50 times per day, 20 minutes per deployment sounds very  
slow for me.

I also cannot reindex data because elasticsearch is the source and the  
only storage for this data, this is statistical data, events that  
happened in the past.

On 26 November 2013 02:59, James Richardson [james.time4tea@gmail.com](mailto:james.time4tea@gmail.com) wrote:

> These 1m items give an index size of about 4gb, for comparison.
> 
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### Author: ![dadoonet](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/dadoonet/32/137187_2.png) [@dadoonet](https://discuss.elastic.co/u/dadoonet)
#### Post date: [November 26, 2013, 6:12am UTC](https://discuss.elastic.co/t/scrolling-performance/14560/5 "2013-11-26T06:12:49Z")

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About injection speed.

Yeah. It depends on the read rate, document size...  
For my demos, I inject 1m docs in less than 1 mn.

But it's directly from a Java program which generate random documents (15 fields).

--  
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Twitter : @dadoonet / @elasticsearchfr / @scrutmydocs

Le 26 nov. 2013 à 06:59, ivan babrou [ibobrik@gmail.com](mailto:ibobrik@gmail.com) a écrit :

20 minutes isn't fast, it's not very fast for sure, you know. We  
deploy up to 50 times per day, 20 minutes per deployment sounds very  
slow for me.

I also cannot reindex data because elasticsearch is the source and the  
only storage for this data, this is statistical data, events that  
happened in the past.

> On 26 November 2013 02:59, James Richardson [james.time4tea@gmail.com](mailto:james.time4tea@gmail.com) wrote:  
> These 1m items give an index size of about 4gb, for comparison.
> 
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### Author: ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)
#### Post date: [November 26, 2013, 6:48pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/6 "2013-11-26T18:48:54Z")

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It would help to have an impression of the source code you use.

Jörg

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### Author: ![Oli\_McCormack](https://avatars.discourse-cdn.com/v4/letter/o/fbc32d/32.png) [@Oli\_McCormack](https://discuss.elastic.co/u/Oli_McCormack)
#### Post date: [November 26, 2013, 7:32pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/7 "2013-11-26T19:32:37Z")

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Is it possible for you to use a scan  
(here[http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-request-search-type.html](http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-request-search-type.html),  
but scroll down the page) with your scroll? It's recommended if you can  
live with point-in-time results - you'll miss docs added/removed to/from  
the index - and a reduced search feature set - for example, sorting.  
However, you'll achieve approximately the same low latency as you iterate  
over the result set.

Or are you experiencing this performance when using scan already?

On Tue, Nov 26, 2013 at 10:48 AM, [joergprante@gmail.com](mailto:joergprante@gmail.com) \<  
[joergprante@gmail.com](mailto:joergprante@gmail.com)\> wrote:

> It would help to have an impression of the source code you use.
> 
> Jörg
> 
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### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [November 26, 2013, 8:23pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/8 "2013-11-26T20:23:29Z")

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I'm using scan already. Is there any other way when there's no unique  
sortable id in every document?

My code looks like this: [http://pastie.org/8510769](http://pastie.org/8510769) (go version)

On 26 November 2013 23:32, Oli McCormack [oli@climate.com](mailto:oli@climate.com) wrote:

> Is it possible for you to use a scan (here, but scroll down the page) with  
> your scroll? It's recommended if you can live with point-in-time results -  
> you'll miss docs added/removed to/from the index - and a reduced search  
> feature set - for example, sorting. However, you'll achieve approximately  
> the same low latency as you iterate over the result set.
> 
> Or are you experiencing this performance when using scan already?
> 
> On Tue, Nov 26, 2013 at 10:48 AM, [joergprante@gmail.com](mailto:joergprante@gmail.com)  
> [joergprante@gmail.com](mailto:joergprante@gmail.com) wrote:
> 
> > It would help to have an impression of the source code you use.
> > 
> > Jörg
> > 
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### Author: ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)
#### Post date: [November 26, 2013, 9:48pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/9 "2013-11-26T21:48:03Z")

</div>

Why do you want to keep search results for 30 minutes on each node?

This is the cause of your program getting slower. In 30 minutes, you can  
easily thrash the system memory of the ES nodes so they must getting slower  
and slower.

Just use a scan/scroll retain time of a few seconds or so, just as long as  
you need to dump the result. But never use minutes (unless you have a good  
reason).

Where do you get this example from?

Jörg

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### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [November 26, 2013, 10:05pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/10 "2013-11-26T22:05:08Z")

</div>

Okay, I changed 30m to 5s. Memory usage was in bounds, I checked it.  
Your version does not explain why restarting scrolling makes it fast  
again. I don't think es could guess that previous scrolling is over.

I didn't get this example from anywhere, I wrote it myself. The first  
version was in php, but it was very slow, so I decided to practice  
golang and wrote this one. This one as slow as previous one.

Btw, results for 5s (no surprise here):

first request: 5000  
fetched: 10000 , time ms: 190  
fetched: 15000 , time ms: 255  
fetched: 20000 , time ms: 197  
fetched: 25000 , time ms: 282  
fetched: 30000 , time ms: 211  
fetched: 35000 , time ms: 213  
fetched: 40000 , time ms: 219  
fetched: 45000 , time ms: 223  
fetched: 50000 , time ms: 231  
fetched: 55000 , time ms: 235  
fetched: 60000 , time ms: 336  
fetched: 65000 , time ms: 344  
fetched: 70000 , time ms: 347  
fetched: 75000 , time ms: 256  
fetched: 80000 , time ms: 357  
fetched: 85000 , time ms: 369  
fetched: 90000 , time ms: 289  
fetched: 95000 , time ms: 305  
fetched: 100000 , time ms: 306  
fetched: 105000 , time ms: 402  
fetched: 110000 , time ms: 296  
fetched: 115000 , time ms: 342  
fetched: 120000 , time ms: 432  
fetched: 125000 , time ms: 430  
fetched: 130000 , time ms: 324  
fetched: 135000 , time ms: 460  
fetched: 140000 , time ms: 352  
fetched: 145000 , time ms: 464  
fetched: 150000 , time ms: 508  
fetched: 155000 , time ms: 523  
fetched: 160000 , time ms: 359  
fetched: 165000 , time ms: 366  
fetched: 170000 , time ms: 409  
fetched: 175000 , time ms: 375  
fetched: 180000 , time ms: 536  
fetched: 185000 , time ms: 392  
fetched: 190000 , time ms: 418  
fetched: 195000 , time ms: 561  
fetched: 200000 , time ms: 418  
fetched: 205000 , time ms: 569  
fetched: 210000 , time ms: 589  
fetched: 215000 , time ms: 460  
fetched: 220000 , time ms: 591  
fetched: 225000 , time ms: 454  
fetched: 230000 , time ms: 486  
fetched: 235000 , time ms: 453  
fetched: 240000 , time ms: 633  
fetched: 245000 , time ms: 656  
fetched: 250000 , time ms: 656  
fetched: 255000 , time ms: 664  
fetched: 260000 , time ms: 488  
fetched: 265000 , time ms: 693  
fetched: 270000 , time ms: 530  
fetched: 275000 , time ms: 510  
fetched: 280000 , time ms: 715  
fetched: 285000 , time ms: 526  
fetched: 290000 , time ms: 578  
fetched: 295000 , time ms: 539  
fetched: 300000 , time ms: 745  
fetched: 305000 , time ms: 757  
fetched: 310000 , time ms: 582  
fetched: 315000 , time ms: 767  
fetched: 320000 , time ms: 628  
fetched: 325000 , time ms: 810  
fetched: 330000 , time ms: 599  
fetched: 335000 , time ms: 615  
fetched: 340000 , time ms: 815  
fetched: 345000 , time ms: 599  
fetched: 350000 , time ms: 660  
fetched: 355000 , time ms: 612  
fetched: 360000 , time ms: 661  
fetched: 365000 , time ms: 894  
fetched: 370000 , time ms: 1058  
fetched: 375000 , time ms: 1112  
fetched: 380000 , time ms: 1128  
fetched: 385000 , time ms: 1127  
fetched: 390000 , time ms: 1153  
fetched: 395000 , time ms: 981  
fetched: 400000 , time ms: 912  
fetched: 405000 , time ms: 958  
fetched: 410000 , time ms: 969  
fetched: 415000 , time ms: 982  
fetched: 420000 , time ms: 727  
fetched: 425000 , time ms: 974  
fetched: 430000 , time ms: 734  
fetched: 435000 , time ms: 843  
fetched: 440000 , time ms: 730  
fetched: 445000 , time ms: 1051  
fetched: 450000 , time ms: 778  
fetched: 455000 , time ms: 773  
fetched: 460000 , time ms: 849  
fetched: 465000 , time ms: 1088  
fetched: 470000 , time ms: 875  
fetched: 475000 , time ms: 807  
fetched: 480000 , time ms: 832  
fetched: 485000 , time ms: 1120  
fetched: 490000 , time ms: 813  
fetched: 495000 , time ms: 1154  
fetched: 500000 , time ms: 806  
fetched: 505000 , time ms: 930  
fetched: 510000 , time ms: 861  
fetched: 515000 , time ms: 1144  
fetched: 520000 , time ms: 885  
fetched: 525000 , time ms: 1197  
fetched: 530000 , time ms: 1205  
fetched: 535000 , time ms: 890  
fetched: 540000 , time ms: 1199  
fetched: 545000 , time ms: 1265  
fetched: 550000 , time ms: 983  
fetched: 555000 , time ms: 1184  
fetched: 560000 , time ms: 954  
fetched: 565000 , time ms: 976  
fetched: 570000 , time ms: 1363  
fetched: 575000 , time ms: 1310  
fetched: 580000 , time ms: 943  
fetched: 585000 , time ms: 1283  
fetched: 590000 , time ms: 1401  
fetched: 595000 , time ms: 985  
fetched: 600000 , time ms: 973  
fetched: 605000 , time ms: 993  
fetched: 610000 , time ms: 1054  
fetched: 615000 , time ms: 1004  
fetched: 620000 , time ms: 994  
fetched: 625000 , time ms: 1021  
fetched: 630000 , time ms: 1406  
fetched: 635000 , time ms: 1044  
fetched: 640000 , time ms: 1051  
fetched: 645000 , time ms: 1123  
fetched: 650000 , time ms: 1080  
fetched: 655000 , time ms: 1070  
fetched: 660000 , time ms: 1037  
fetched: 665000 , time ms: 1191  
fetched: 670000 , time ms: 1466  
fetched: 675000 , time ms: 1167

And after immediate ctrl+c and dumping restart:

first request: 5000  
fetched: 10000 , time ms: 229  
fetched: 15000 , time ms: 221  
fetched: 20000 , time ms: 225  
fetched: 25000 , time ms: 232  
fetched: 30000 , time ms: 304  
fetched: 35000 , time ms: 331  
fetched: 40000 , time ms: 248  
fetched: 45000 , time ms: 255  
fetched: 50000 , time ms: 264  
fetched: 55000 , time ms: 314  
fetched: 60000 , time ms: 329  
fetched: 65000 , time ms: 304  
fetched: 70000 , time ms: 296  
fetched: 75000 , time ms: 286  
fetched: 80000 , time ms: 409  
fetched: 85000 , time ms: 411  
fetched: 90000 , time ms: 304  
fetched: 95000 , time ms: 427  
fetched: 100000 , time ms: 310  
fetched: 105000 , time ms: 315  
fetched: 110000 , time ms: 406

On 27 November 2013 01:48, [joergprante@gmail.com](mailto:joergprante@gmail.com) [joergprante@gmail.com](mailto:joergprante@gmail.com) wrote:

> Why do you want to keep search results for 30 minutes on each node?
> 
> This is the cause of your program getting slower. In 30 minutes, you can  
> easily thrash the system memory of the ES nodes so they must getting slower  
> and slower.
> 
> Just use a scan/scroll retain time of a few seconds or so, just as long as  
> you need to dump the result. But never use minutes (unless you have a good  
> reason).
> 
> Where do you get this example from?
> 
> Jörg
> 
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### Author: ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)
#### Post date: [November 26, 2013, 10:26pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/11 "2013-11-26T22:26:12Z")

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You have all documents of same size?

And you can confirm the network interface bandwidth is not exhausted?

Jörg

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### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [November 26, 2013, 10:29pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/12 "2013-11-26T22:29:57Z")

</div>

Exhausting gigabit network is hard enough, we have small documets. If you  
look at the code, you may notice that I print timer from es so even 56k  
modem to the client should make no difference.

On Wednesday, November 27, 2013, [joergprante@gmail.com](mailto:joergprante@gmail.com) wrote:

> You have all documents of same size?
> 
> And you can confirm the network interface bandwidth is not exhausted?
> 
> Jörg
> 
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### Author: ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)
#### Post date: [November 27, 2013, 12:47am UTC](https://discuss.elastic.co/t/scrolling-performance/14560/13 "2013-11-27T00:47:59Z")

</div>

On my test 0.90.5 ES node with a modified knapsack plugin, I observe  
constant "took" numbers in scan/scroll.

See gist: [https://gist.github.com/jprante/7668933](https://gist.github.com/jprante/7668933)

Each line fetches 1000 docs of an avg doc size of ~1k.

Jörg

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### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [November 27, 2013, 10:30am UTC](https://discuss.elastic.co/t/scrolling-performance/14560/14 "2013-11-27T10:30:50Z")

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How many items do you have in your index? Which java version do you use?

On 27 November 2013 04:47, [joergprante@gmail.com](mailto:joergprante@gmail.com) [joergprante@gmail.com](mailto:joergprante@gmail.com) wrote:

> On my test 0.90.5 ES node with a modified knapsack plugin, I observe  
> constant "took" numbers in scan/scroll.
> 
> See gist: [Took times on 0.90.5 with scan/scroll, each step = 1000 docs of ~1k · GitHub](https://gist.github.com/jprante/7668933)
> 
> Each line fetches 1000 docs of an avg doc size of ~1k.
> 
> Jörg
> 
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### Author: ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)
#### Post date: [November 27, 2013, 2:03pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/15 "2013-11-27T14:03:46Z")

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I executed a scan/scroll over 60 million docs, size of the indices (folder  
'data' size) is 87G.

java version "1.7.0\_25"  
Java(TM) SE Runtime Environment (build 1.7.0\_25-b15)  
Java HotSpot(TM) 64-Bit Server VM (build 23.25-b01, mixed mode)

Heap is 2G

Red Hat Enterprise Linux Server release 6.4 (Santiago)

Jörg

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### Author: ![LiquidMark](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/liquidmark/32/1151_2.png) [@LiquidMark](https://discuss.elastic.co/u/LiquidMark)
#### Post date: [January 19, 2014, 5:49pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/16 "2014-01-19T17:49:38Z")

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Hi Jörg,

It looks like you know something about scan/scroll I haven't found  
documented elsewhere -- how to scan 60 million docs with 1000 documents per  
fetch, at constant time per fetch. Other comments I've seen indicate that,  
the deeper you get into fetching the results, the slower each fetch gets.  
I'm looking at alternatives for implementing a feature which will require  
scan/scroll on a similar scale, and knowing that what you've done is  
possible is critical for my planning. Could you please share the key parts  
of your setup/retrieve code, in addition to the configuration / version  
information you've already shared?

Thanks in advance,

-Mark

On Wednesday, November 27, 2013 8:03:46 AM UTC-6, Jörg Prante wrote:

> I executed a scan/scroll over 60 million docs, size of the indices (folder  
> 'data' size) is 87G.
> 
> java version "1.7.0\_25"  
> Java(TM) SE Runtime Environment (build 1.7.0\_25-b15)  
> Java HotSpot(TM) 64-Bit Server VM (build 23.25-b01, mixed mode)
> 
> Heap is 2G
> 
> Red Hat Enterprise Linux Server release 6.4 (Santiago)
> 
> Jörg

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### Author: ![Ivan\_Babrou](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/ivan_babrou/32/1854_2.png) [@Ivan\_Babrou](https://discuss.elastic.co/u/Ivan_Babrou)
#### Post date: [January 19, 2014, 6:28pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/17 "2014-01-19T18:28:48Z")

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Mark, my scrolling performance is pretty constant now too. My problem  
was in incorrect code, actually. You could check out correct version  
here: [https://github.com/bobrik/esreindexer/blob/master/reindexer.go](https://github.com/bobrik/esreindexer/blob/master/reindexer.go)

On 19 January 2014 21:49, LiquidMark [mark.e.molloy@gmail.com](mailto:mark.e.molloy@gmail.com) wrote:

> Hi Jörg,
> 
> It looks like you know something about scan/scroll I haven't found  
> documented elsewhere -- how to scan 60 million docs with 1000 documents per  
> fetch, at constant time per fetch. Other comments I've seen indicate that,  
> the deeper you get into fetching the results, the slower each fetch gets.  
> I'm looking at alternatives for implementing a feature which will require  
> scan/scroll on a similar scale, and knowing that what you've done is  
> possible is critical for my planning. Could you please share the key parts  
> of your setup/retrieve code, in addition to the configuration / version  
> information you've already shared?
> 
> Thanks in advance,
> 
> -Mark
> 
> On Wednesday, November 27, 2013 8:03:46 AM UTC-6, Jörg Prante wrote:
> 
> > I executed a scan/scroll over 60 million docs, size of the indices (folder  
> > 'data' size) is 87G.
> > 
> > java version "1.7.0\_25"  
> > Java(TM) SE Runtime Environment (build 1.7.0\_25-b15)  
> > Java HotSpot(TM) 64-Bit Server VM (build 23.25-b01, mixed mode)
> > 
> > Heap is 2G
> > 
> > Red Hat Enterprise Linux Server release 6.4 (Santiago)
> > 
> > Jörg
> 
> --  
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--  
Regards, Ian Babrou  
[http://bobrik.name](http://bobrik.name) [http://twitter.com/ibobrik](http://twitter.com/ibobrik) skype:i.babrou

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### Author: ![LiquidMark](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/liquidmark/32/1151_2.png) [@LiquidMark](https://discuss.elastic.co/u/LiquidMark)
#### Post date: [January 19, 2014, 7:49pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/18 "2014-01-19T19:49:09Z")

</div>

Hi Jörg, Thanks for sharing!

What kind of elaspsed time (in milliseconds?), roughly, does a  
1000-document fetch take for you? Can you tell me key info that you thinks  
affects this for you, e.g. how many shards etc?

-Mark

On Sunday, January 19, 2014 12:28:48 PM UTC-6, Ivan Babrou wrote:

> Mark, my scrolling performance is pretty constant now too. My problem  
> was in incorrect code, actually. You could check out correct version  
> here: [https://github.com/bobrik/esreindexer/blob/master/reindexer.go](https://github.com/bobrik/esreindexer/blob/master/reindexer.go)
> 
> On 19 January 2014 21:49, LiquidMark \<[mark.e...@gmail.com](mailto:mark.e...@gmail.com) \<javascript:\>\>  
> wrote:
> 
> > Hi Jörg,
> > 
> > It looks like you know something about scan/scroll I haven't found  
> > documented elsewhere -- how to scan 60 million docs with 1000 documents  
> > per  
> > fetch, at constant time per fetch. Other comments I've seen indicate  
> > that,  
> > the deeper you get into fetching the results, the slower each fetch  
> > gets.  
> > I'm looking at alternatives for implementing a feature which will  
> > require  
> > scan/scroll on a similar scale, and knowing that what you've done is  
> > possible is critical for my planning. Could you please share the key  
> > parts  
> > of your setup/retrieve code, in addition to the configuration / version  
> > information you've already shared?
> > 
> > Thanks in advance,
> > 
> > -Mark
> > 
> > On Wednesday, November 27, 2013 8:03:46 AM UTC-6, Jörg Prante wrote:
> > 
> > > I executed a scan/scroll over 60 million docs, size of the indices  
> > > (folder  
> > > 'data' size) is 87G.
> > > 
> > > java version "1.7.0\_25"  
> > > Java(TM) SE Runtime Environment (build 1.7.0\_25-b15)  
> > > Java HotSpot(TM) 64-Bit Server VM (build 23.25-b01, mixed mode)
> > > 
> > > Heap is 2G
> > > 
> > > Red Hat Enterprise Linux Server release 6.4 (Santiago)
> > > 
> > > Jörg
> > 
> > --  
> > You received this message because you are subscribed to a topic in the  
> > Google Groups "elasticsearch" group.  
> > To unsubscribe from this topic, visit  
> > [https://groups.google.com/d/topic/elasticsearch/RYVP-VH8BaA/unsubscribe](https://groups.google.com/d/topic/elasticsearch/RYVP-VH8BaA/unsubscribe).
> 
> > To unsubscribe from this group and all its topics, send an email to  
> > [elasticsearc...@googlegroups.com](mailto:elasticsearc...@googlegroups.com) \<javascript:\>.  
> > To view this discussion on the web visit
> 
> [https://groups.google.com/d/msgid/elasticsearch/705ede01-a19e-4c40-94d4-2e592de72303%40googlegroups.com](https://groups.google.com/d/msgid/elasticsearch/705ede01-a19e-4c40-94d4-2e592de72303%40googlegroups.com).
> 
> > For more options, visit [https://groups.google.com/groups/opt\_out](https://groups.google.com/groups/opt_out).
> 
> --  
> Regards, Ian Babrou  
> [http://bobrik.name](http://bobrik.name) [http://twitter.com/ibobrik](http://twitter.com/ibobrik) skype:i.babrou

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### Author: ![jprante](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jprante/32/44941_2.png) [@jprante](https://discuss.elastic.co/u/jprante)
#### Post date: [January 19, 2014, 8:29pm UTC](https://discuss.elastic.co/t/scrolling-performance/14560/19 "2014-01-19T20:29:01Z")

</div>

The absolute time taken depends on the cluster resources of course. At my  
laptop, for 1000 docs of ~1k size in average, a scroll response 'took'  
field shows usually ~200-500ms. It takes additional time to process the  
response hits.

I am not sure if the number of shards is relevant. There are more important  
factors: shard numbers per node, shard size, buffers and heap memory,  
network compression, network speed, node workload...

If you are interested in a Java scan/scroll example, you can peek into the  
knapsack plugin source

[https://github.com/jprante/elasticsearch-knapsack/blob/master/src/main/java/org/xbib/elasticsearch/action/RestExportAction.java#L310](https://github.com/jprante/elasticsearch-knapsack/blob/master/src/main/java/org/xbib/elasticsearch/action/RestExportAction.java#L310)

Critical for a scalable scan/scroll is a reasonable timeout. In the  
knapsack plugin, I use a default of 30 seconds.

In the ES docs, a timeout of 10 minutes is used

[http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-request-search-type.html](http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-request-search-type.html)

which seems not very helpful, as this will pressure your heap in almost all  
cases of long-lasting scan/scroll...

Jörg

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### Author: ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)
#### Post date: [July 6, 2017, 1:55am UTC](https://discuss.elastic.co/t/scrolling-performance/14560/20 "2017-07-06T01:55:59Z")

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