 Austrian sculptor Mathias Purkarthofer and was unveiled, along with the other 7 statues that were located on the Elisabeth Bridge in 1867.
The statues were moved when the Elisabeth Bridge was demolished in 1897 and eventually relocated to their current site lining the path to the Rathaus in 1902.
One of the interesting monuments at Rathausplatz is that of Nicholas Count of Salm (Niklas Graf Salm), German commander and defender of the city of Vienna during the first siege by the Turks in 1529.
The statue is of a strong and confident Nicholas, dressed in a military attire of the era, with sword in his left hand, peering forward. It is a fine image of the historical figure and an interesting.
You will find it in line with other monuments to important figures, leading up to Rathaus. Give it a few minutes while you are monument viewing in the area. There are quite a few to see here at Rathausplatz along with Niklas Graf Salm.
Welche Hotels gibt es in der Nähe von Statue Niklas Graf Salm?
Sehen Sie sich alle Hotels in der Nähe von Statue Niklas Graf Salm auf Tripadvisor an.
Welche Restaurants gibt es in der Nähe von Statue Niklas Graf Salm?
Sehen Sie sich alle Restaurants in der Nähe von Statue Niklas Graf Salm auf Tripadvisor an.The Australian economy contracted 0.3 per cent in 2019-20, according to figures released by the Australian Bureau of Statistics (ABS) today. Head of National Accounts at the ABS, Michael Smedes said: “Australia's annual economic activity fell for the first time since 1990-91, the onset of the COVID-19 pandemic ended 28 years of consecutive growth".
The Annual National Accounts provides further insights on the structure of the economy, using the latest economy wide supply and use data. Mr Smedes, added: "In 2019-20 the largest industries in the Australian economy were Mining, Financial and Insurance Services, Health Care and Social Assistance and Construction, representing over a third of the economy. The Mining industry continued to expand, recording its 16th consecutive annual growth, which reflected increased oil and gas production".
The annual accounts also provide key indicators from balance sheets and productivity estimates. Australia’s labour productivity rose 0.5 per cent in 2019-20, below its 10 year average of 1.0 per cent, with falls recorded in 11 out of 19 industries.
Household net worth increased $485 billion to $11.1 trillion in 2019-20, with a $91 billion increase in cash and deposits and $375 billion increase in land value.The Babylon Union Free School District is firmly committed to implementing, supporting, and evaluating a school educational plan for Shared Decision Making which will generate a spirit of collaboration and promote the achievement of excellence in all phases of school life for each member of the school community.
Each of our school teams is represented by board members, administrators, teachers, non-teaching staff, parents, community members, and on the Junior / Senior High School team, students. Teams meet approximately once a month and maintain agendas and minutes. The following categories have been established as areas of discussion for the Site Based Teams: Curriculum, Educational Accountability, Behavioral Management, Facilities, Fiscal Considerations and Communication. The scope of such discussions should be focused on the improved educational performance of our students.
Q: Slow performance and index not taken into consideration in PostgreSQL I'll post my query plan, view and indexes at the bottom of the page so that I can keep this question as clean as possible.
The issue I have is slow performance for a view that is not using indexes as I would expect them to be used. I have a table with around 7 million rows that I use as source for the view below.
I have added an index on eventdate which is being used as expected, but why is the index on manufacturerkey ignored? Which indexes would be more efficient?
Also, is it maybe this part  to_char(fe.eventdate, 'HH24:MI'::text) AS hourminutes that hurts the performance?
Query plan: https://explain.dalibo.com/plan/Pvw
CREATE OR REPLACE VIEW public.v_test
AS SELECT df.facilityname,
    dd.date,
    dt.military_hour AS hour,
    to_char(fe.eventdate, 'HH24:MI'::text) AS hourminutes,
    df.tenantid,
    df.tenantname,
    dev.name AS event_type_name,
    dtt.name AS ticket_type_name,
    dde.name AS device_type_name,
    count(*) AS count,
    dl.country,
    dl.state,
    dl.district,
    ds.systemmanufacturer
   FROM fact_entriesexits fe
     JOIN dim_facility df ON df.key = fe.facilitykey
     JOIN dim_date dd ON dd.key = fe.datekey
     JOIN dim_time dt ON dt.key = fe.timekey
     LEFT JOIN dim_device dde ON dde.key = fe.devicekey
     JOIN dim_eventtype dev ON dev.key = fe.eventtypekey
     JOIN dim_tickettype dtt ON dtt.key = fe.tickettypekey
     JOIN dim_licenseplate dl ON dl.key = fe.licenseplatekey
     LEFT JOIN dim_systeminterface ds ON ds.key = fe.systeminterfacekey
  WHERE fe.manufacturerkey = ANY (ARRAY[2, 1])
  AND fe.eventdate >= '2022-01-01'
  GROUP BY df.tenantname, df.tenantid, dl.region, dl.country, dl.state, 
  dl.district, df.facilityname, dev.name, dtt.name, dde.name,
  ds.systemmanufacturer, dd.date, dt.military_hour, (to_char(fe.eventdate, 'HH24:MI'::text)), fe.licenseplatekey;

Here are the indexes the table fact_entriesexits contains:
CREATE INDEX idx_devicetype_fact_entriesexits_202008 ON public.fact_entriesexits_202008 USING btree (devicetype)
CREATE INDEX idx_etlsource_fact_entriesexits_202008 ON public.fact_entriesexits_202008 USING btree (etlsource)
CREATE INDEX idx_eventdate_fact_entriesexits_202008 ON public.fact_entriesexits_202008 USING btree (eventdate)
CREATE INDEX idx_fact_entriesexits_202008 ON public.fact_entriesexits_202008 USING btree (datekey)
CREATE INDEX idx_manufacturerkey_202008 ON public.fact_entriesexits_202008 USING btree (manufacturerkey)

Query plan:
Subquery Scan on v_lpr2  (cost=505358.60..508346.26 rows=17079 width=340) (actual time=85619.542..109797.440 rows=3008065 loops=1)
  Buffers: shared hit=91037 read=366546, temp read=83669 written=83694
  ->  Finalize GroupAggregate  (cost=505358.60..508175.47 rows=17079 width=359) (actual time=85619.539..109097.943 rows=3008065 loops=1)
        Group Key: df.tenantname, df.tenantid, dl.region, dl.country, dl.state, dl.district, df.facilityname, dev.name, dtt.name, dde.name, ds.systemmanufacturer, dd.date, dt.military_hour, (to_char(fe.eventdate, 'HH24:MI'::text)), fe.licenseplatekey
        Buffers: shared hit=91037 read=366546, temp read=83669 written=83694
        ->  Gather Merge  (cost=505358.60..507392.70 rows=14232 width=359) (actual time=85619.507..105395.429 rows=3308717 loops=1)
              Workers Planned: 2
              Workers Launched: 2
              Buffers: shared hit=91037 read=366546, temp read=83669 written=83694
              ->  Partial GroupAggregate  (cost=504358.57..504749.95 rows=7116 width=359) (actual time=85169.770..94043.715 rows=1102906 loops=3)
                    Group Key: df.tenantname, df.tenantid, dl.region, dl.country, dl.state, dl.district, df.facilityname, dev.name, dtt.name, dde.name, ds.systemmanufacturer, dd.date, dt.military_hour, (to_char(fe.eventdate, 'HH24:MI'::text)), fe.licenseplatekey
                    Buffers: