#acl All:read
= Results for Exercise Sheet 5 (q-Gram Index) =
Add your row to the table below, following the examples already there. In the first column, write your account name, or name1+name2 if you work in a group.

For each query, write down the total query time (''Time''), the number of needed PED computations (''#PED'') and the number of returned results (''#RES''). In the last two columns, give details about the provided PED module you are using (either ped_c or ped_python) and your local machine.
||<tablewidth="&quot" tableheight="&quot" tablestyle="&quot; &amp; quot;  &amp; amp;  quot;   100%&amp; amp;  amp;   quot;   ;   auto&amp; amp;  amp;   quot&amp; amp;  quot;   ;  &amp; amp;  amp;  quot&amp; amp;  quot;  ;  &amp; amp;  amp;  quot&amp; amp;  quot&amp; quot;  ; &amp; amp; quot&amp; quot; ; &amp; amp; quot&amp; quot&quot; ;&amp;quot&quot;;&amp;quot&quot"style="&quot; &amp; quot;  &amp; amp;  quot;   &amp; amp;  amp;   quot;text-align:center&amp; amp;  amp;   quot;   &amp; amp;  quot;  &amp; quot; &quot;" |2>'''Name''' ||||||<style="&quot; &amp; quot;  &amp; amp;  quot;text-align:center&amp; amp;  quot;  &amp; quot; &quot;">'''Query: the''' ||||||<style="&quot; &amp; quot;  &amp; amp;  quot;text-align:center&amp; amp;  quot;  &amp; quot; &quot;">'''Query: asdf''' ||||||<style="&quot; &amp; quot;  &amp; amp;  quot;text-align:center&amp; amp;  quot;  &amp; quot; &quot;">'''Query: the shanksha redemption''' ||<style="&quot; &amp; quot;  &amp; amp;  quot;text-align:center&amp; amp;  quot;  &amp; quot; &quot;" |2>'''PED Module''' ||||<style="&quot; &amp; quot;  &amp; amp;  quot;text-align:center&amp; amp;  quot;  &amp; quot; &quot;" |2>'''Processor / RAM''' ||
||'''Time''' ||'''#PED''' ||'''#RES''' ||'''Time''' ||'''#PED''' ||'''#RES''' ||'''Time''' ||'''#PED''' ||'''#RES''' ||
||np1042 ||ms ||47026 ||46182 ||235ms ||238294 ||335 ||542ms ||2204 ||1 ||ped_c ||Intel Core i5-7300U CPU @ 2.60GHz, 12 GB RAM ||
||np1042 ||915ms ||47026 ||46182 ||4325ms ||238294 ||335 ||1904ms ||2204 ||1 ||ped_python ||Intel Core i5-7300U CPU @ 2.60GHz, 12 GB RAM ||